{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,8]],"date-time":"2025-01-08T05:33:32Z","timestamp":1736314412506,"version":"3.32.0"},"reference-count":227,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2021,11,26]],"date-time":"2021-11-26T00:00:00Z","timestamp":1637884800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"H2020 European project ADE","award":["821988"]},{"name":"Andalusian regional government","award":["P18-RT-991"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path planners that enable the robot to deliberate about how to move from its location at one moment to another. Looking for the most appropriate path planning algorithm according to the requirements imposed by users can be challenging, given the overwhelming number of approaches that exist in the literature. Moreover, the past review works analyzed here cover only some of these approaches, missing important ones. For this reason, our paper aims to serve as a starting point for a clear and comprehensive overview of the research to date. It introduces a global classification of path planning algorithms, with a focus on those approaches used along with autonomous ground vehicles, but is also extendable to other robots moving on surfaces, such as autonomous boats. Moreover, the models used to represent the environment, together with the robot mobility and dynamics, are also addressed from the perspective of path planning. Each of the path planning categories presented in the classification is disclosed and analyzed, and a discussion about their applicability is added at the end.<\/jats:p>","DOI":"10.3390\/s21237898","type":"journal-article","created":{"date-parts":[[2021,12,1]],"date-time":"2021-12-01T06:45:02Z","timestamp":1638341102000},"page":"7898","source":"Crossref","is-referenced-by-count":188,"title":["Path Planning for Autonomous Mobile Robots: A Review"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5130-3808","authenticated-orcid":false,"given":"Jos\u00e9 Ricardo","family":"S\u00e1nchez-Ib\u00e1\u00f1ez","sequence":"first","affiliation":[{"name":"Space Robotics Laboratory, Department of Systems Engineering and Automation, Universidad de M\u00e1laga, C\/Ortiz Ramos s\/n, 29071 M\u00e1laga, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5819-8310","authenticated-orcid":false,"given":"Carlos J.","family":"P\u00e9rez-del-Pulgar","sequence":"additional","affiliation":[{"name":"Space Robotics Laboratory, Department of Systems Engineering and Automation, Universidad de M\u00e1laga, C\/Ortiz Ramos s\/n, 29071 M\u00e1laga, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3432-3230","authenticated-orcid":false,"given":"Alfonso","family":"Garc\u00eda-Cerezo","sequence":"additional","affiliation":[{"name":"Space Robotics Laboratory, Department of Systems Engineering and Automation, Universidad de M\u00e1laga, C\/Ortiz Ramos s\/n, 29071 M\u00e1laga, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,26]]},"reference":[{"key":"ref_1","first-page":"88507","article-title":"Optimal Path Planning for a Remote Sensing Unmanned Ground Vehicle in a Hazardous Indoor Environment","volume":"9","author":"Alenezi","year":"2018","journal-title":"Intell. Control Autom."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ishigami, G., Nagatani, K., and Yoshida, K. (2011, January 25\u201330). Path planning and evaluation for planetary rovers based on dynamic mobility index. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6094768"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.5897\/IJPS11.1745","article-title":"Optimal path planning of mobile robots: A review","volume":"7","author":"Raja","year":"2012","journal-title":"Int. J. Phys. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, H.Y., Lin, W.M., and Chen, A.X. (2018). Path planning for the mobile robot: A review. Symmetry, 10.","DOI":"10.3390\/sym10100450"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhang, F., Li, N., Xue, T., Zhu, Y., Yuan, R., and Fu, Y. (2019, January 6\u20138). An Improved Dynamic Window Approach Integrated Global Path Planning. Proceedings of the 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO), Dali, China.","DOI":"10.1109\/ROBIO49542.2019.8961684"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1007\/s00773-020-00787-6","article-title":"Path planning and collision avoidance for autonomous surface vehicles I: A review","volume":"26","author":"Vagale","year":"2021","journal-title":"J. Mar. Sci. Technol."},{"key":"ref_7","unstructured":"Souissi, O., Benatitallah, R., Duvivier, D., Artiba, A., Belanger, N., and Feyzeau, P. (2013, January 28\u201330). Path planning: A 2013 survey. Proceedings of the 2013 International Conference on Industrial Engineering and Systems Management (IESM), Rabat, Morocco."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.robot.2016.08.001","article-title":"Heuristic approaches in robot path planning: A survey","volume":"86","author":"Mac","year":"2016","journal-title":"Robot. Auton. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.procs.2018.07.018","article-title":"Methodology for path planning and optimization of mobile robots: A review","volume":"133","author":"Zafar","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.dt.2019.04.011","article-title":"A review: On path planning strategies for navigation of mobile robot","volume":"15","author":"Patle","year":"2019","journal-title":"Def. Technol."},{"key":"ref_11","first-page":"85","article-title":"Any-angle path planning","volume":"34","author":"Nash","year":"2013","journal-title":"AI Mag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/ACCESS.2014.2302442","article-title":"Sampling-based robot motion planning: A review","volume":"2","author":"Elbanhawi","year":"2014","journal-title":"IEEE Access"},{"key":"ref_13","first-page":"1135","article-title":"A review of motion planning techniques for automated vehicles","volume":"17","author":"Nashashibi","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","first-page":"97","article-title":"Optimal path planning using RRT* based approaches: A survey and future directions","volume":"7","author":"Noreen","year":"2016","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Injarapu, A.S.H.H.V., and Gawre, S.K. (2017, January 27\u201329). A survey of autonomous mobile robot path planning approaches. Proceedings of the 2017 International Conference on Recent Innovations in Signal Processing and Embedded Systems (RISE), Bhopal, India.","DOI":"10.1109\/RISE.2017.8378228"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Ravankar, A., Ravankar, A.A., Kobayashi, Y., Hoshino, Y., and Peng, C.C. (2018). Path smoothing techniques in robot navigation: State-of-the-art, current and future challenges. Sensors, 18.","DOI":"10.3390\/s18093170"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Costa, M.M., and Silva, M.F. (2019, January 24\u201326). A survey on path planning algorithms for mobile robots. Proceedings of the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Cosme, Portugal.","DOI":"10.1109\/ICARSC.2019.8733623"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"39005","DOI":"10.1109\/ACCESS.2019.2906782","article-title":"Fast methods for eikonal equations: An experimental survey","volume":"7","author":"Garrido","year":"2019","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Campbell, S., O\u2019Mahony, N., Carvalho, A., Krpalkova, L., Riordan, D., and Walsh, J. (2020, January 12\u201315). Path planning techniques for mobile robots a review. Proceedings of the 2020 6th International Conference on Mechatronics and Robotics Engineering (ICMRE), Barcelona, Spain.","DOI":"10.1109\/ICMRE49073.2020.9065187"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1108\/IR-03-2020-0063","article-title":"A survey of energy-efficient motion planning for wheeled mobile robots","volume":"47","author":"Zhang","year":"2020","journal-title":"Ind. Robot. Int. J. Robot. Res. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"69061","DOI":"10.1109\/ACCESS.2021.3076530","article-title":"Motion planning for mobile Robots\u2013focusing on deep reinforcement learning: A systematic Review","volume":"9","author":"Sun","year":"2021","journal-title":"IEEE Access"},{"key":"ref_22","first-page":"18","article-title":"Map representation for robots","volume":"2","author":"Yi","year":"2012","journal-title":"Smart Comput. Rev."},{"key":"ref_23","first-page":"7","article-title":"A comprehensive study on pathfinding techniques for robotics and video games","volume":"2015","author":"Algfoor","year":"2015","journal-title":"Int. J. Comput. Games Technol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Petres, C., Pailhas, Y., Petillot, Y., and Lane, D. (2005, January 20\u201323). Underwater path planing using fast marching algorithms. Proceedings of the Oceans 2005-Europe, Brest, France.","DOI":"10.1109\/OCEANSE.2005.1513161"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1109\/21.148426","article-title":"Numerical potential field techniques for robot path planning","volume":"22","author":"Barraquand","year":"1992","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_26","unstructured":"Huang, H.P., and Chung, S.Y. (October, January 28). Dynamic visibility graph for path planning. Proceedings of the 2004 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No. 04CH37566), Sendai, Japan."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1177\/0278364909340445","article-title":"Planning long dynamically feasible maneuvers for autonomous vehicles","volume":"28","author":"Likhachev","year":"2009","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1109\/TIV.2020.2991951","article-title":"Improved path planning by tightly combining lattice-based path planning and optimal control","volume":"6","author":"Bergman","year":"2020","journal-title":"IEEE Trans. Intell. Veh."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Choi, S., Park, J., Lim, E., and Yu, W. (2012, January 26\u201328). Global path planning on uneven elevation maps. Proceedings of the 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Daejeon, Korea.","DOI":"10.1109\/URAI.2012.6462928"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1016\/j.engappai.2013.01.006","article-title":"Terrain traversability analysis methods for unmanned ground vehicles: A survey","volume":"26","author":"Papadakis","year":"2013","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.robot.2015.02.003","article-title":"Direction-dependent optimal path planning for autonomous vehicles","volume":"70","author":"Shum","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Papadopoulos, E., and Misailidis, M. (2007, January 2\u20135). On differential drive robot odometry with application to path planning. Proceedings of the 2007 European Control Conference (ECC), Kos, Greece.","DOI":"10.23919\/ECC.2007.7068785"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1007\/s42423-018-0007-3","article-title":"Initial design characteristics, testing and performance optimisation for a lunar exploration micro-rover prototype","volume":"1","author":"Tamakoshi","year":"2018","journal-title":"Adv. Astronaut. Sci. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1109\/TMECH.2013.2277271","article-title":"Event-based localization in ackermann steering limited resource mobile robots","volume":"19","author":"Marin","year":"2013","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mandow, A., Martinez, J.L., Morales, J., Blanco, J.L., Garcia-Cerezo, A., and Gonzalez, J. (November, January 29). Experimental kinematics for wheeled skid-steer mobile robots. Proceedings of the 2007 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA.","DOI":"10.1109\/IROS.2007.4399139"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wu, M., Dai, S.L., and Yang, C. (2020). Mixed reality enhanced user interactive path planning for omnidirectional mobile robot. Appl. Sci., 10.","DOI":"10.3390\/app10031135"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1007\/s10915-012-9671-y","article-title":"Optimal trajectories of curvature constrained motion in the hamilton\u2013jacobi formulation","volume":"54","author":"Takei","year":"2013","journal-title":"J. Sci. Comput."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/s10846-020-01173-5","article-title":"Considering slip-track for energy-efficient paths of skid-steer rovers","volume":"100","author":"Effati","year":"2020","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.jterra.2010.02.004","article-title":"The ExoMars rover locomotion subsystem","volume":"47","author":"Patel","year":"2010","journal-title":"J. Terramech."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Rohmer, E., Yoshida, T., Ohno, K., Nagatani, K., Tadokoro, S., and Konayagi, E. (2010). Quince: A collaborative mobile robotic platform for rescue robots research and development. The Abstracts of the International Conference on Advanced Mechatronics: Toward Evolutionary Fusion of IT and Mechatronics: ICAM 2010.5, The Japan Society of Mechanical Engineers.","DOI":"10.1299\/jsmeicam.2010.5.225"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.robot.2014.09.003","article-title":"Design and comparative evaluation of an iterative contact point estimation method for static stability estimation of mobile actively reconfigurable robots","volume":"63","author":"Brunner","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_42","unstructured":"Azkarate, M., Zwick, M., Hidalgo-Carrio, J., Nelen, R., Wiese, T., Poulakis, P., Joudrier, L., and Visentin, G. (2015, January 11\u201313). First Experimental investigations on Wheel-Walking for improving Triple-Bogie rover locomotion performances. Proceedings of the 13th Symposium on Advanced Space Technologies in Robotics and Automation, Noordwijk, The Netherlands."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.3103\/S1068798X17120127","article-title":"Wheel-walking propulsion unit of a planetary rover with active suspension","volume":"37","author":"Malenkov","year":"2017","journal-title":"Russ. Eng. Res."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Moreland, S., Skonieczny, K., Wettergreen, D., Asnani, V., Creager, C., and Oravec, H. (2011, January 5\u201312). Inching locomotion for planetary rover mobility. Proceedings of the 2011 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2011.5747265"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Creager, C., Moreland, S., Skonieczny, K., Johnson, K., Asnani, V., and Gilligan, R. (2012, January 15\u201318). Benefit of \u201cPush-Pull\u201d Locomotion for Planetary Rover Mobility. Proceedings of the Thirteenth ASCE Aerospace Division Conference on Engineering, Science, Construction, and Operations in Challenging Environments, and the 5th NASA\/ASCE Workshop On Granular Materials in Space Exploration, Pasadena, CA, USA.","DOI":"10.1061\/9780784412190.002"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.jterra.2014.12.001","article-title":"Push\u2013pull locomotion for vehicle extrication","volume":"57","author":"Creager","year":"2015","journal-title":"J. Terramech."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1163\/016918610X501499","article-title":"Dynamic Simulation-Based Action Planner for a Reconfigurable Hybrid Leg\u2013Wheel Planetary Exploration Rover","volume":"24","author":"Rohmer","year":"2010","journal-title":"Adv. Robot."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"P\u00e9rez-del Pulgar, C.J., S\u00e1nchez, J., S\u00e1nchez, A., Azkarate, M., and Visentin, G. (2017, January 3\u20137). Path planning for reconfigurable rovers in planetary exploration. Proceedings of the 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Munich, Germany.","DOI":"10.1109\/AIM.2017.8014223"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.engappai.2019.08.011","article-title":"Dynamic path planning for reconfigurable rovers using a multi-layered grid","volume":"86","author":"Azkarate","year":"2019","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1002\/rob.21894","article-title":"Sampling-based hierarchical motion planning for a reconfigurable wheel-on-leg planetary analogue exploration rover","volume":"37","author":"Reid","year":"2019","journal-title":"J. Field Robot."},{"key":"ref_51","first-page":"100","article-title":"Modeling slope in a geographic information system","volume":"58","author":"Mattson","year":"2004","journal-title":"J. Ark. Acad. Sci."},{"key":"ref_52","unstructured":"Mir\u00f3, J.V., Dumonteil, G., Beck, C., and Dissanayake, G. (2010, January 18\u201322). A kyno-dynamic metric to plan stable paths over uneven terrain. Proceedings of the 2010 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s10846-017-0495-8","article-title":"Planning stable and efficient paths for reconfigurable robots on uneven terrain","volume":"87","author":"Norouzi","year":"2017","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1109\/70.62043","article-title":"Optimal grid-free path planning across arbitrarily-contoured terrain with anisotropic friction and gravity effects","volume":"6","author":"Rowe","year":"1990","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1109\/TII.2015.2413355","article-title":"A constraint-aware heuristic path planner for finding energy-efficient paths on uneven terrains","volume":"11","author":"Ganganath","year":"2015","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"4264","DOI":"10.1109\/TII.2018.2844370","article-title":"Shortest path planning for energy-constrained mobile platforms navigating on uneven terrains","volume":"14","author":"Ganganath","year":"2018","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Gruning, V., Pentzer, J., Brennan, S., and Reichard, K. (2020, January 1\u20133). Energy-Aware Path Planning for Skid-Steer Robots Operating on Hilly Terrain. Proceedings of the 2020 American Control Conference (ACC), Denver, CO, USA.","DOI":"10.23919\/ACC45564.2020.9147470"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1002\/rob.21700","article-title":"Driving on point clouds: Motion planning, trajectory optimization, and terrain assessment in generic nonplanar environments","volume":"34","author":"Furgale","year":"2017","journal-title":"J. Field Robot."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Lindsay, J.B., Newman, D.R., and Francioni, A. (2019). Scale-Optimized Surface Roughness for Topographic Analysis. Geosciences, 9.","DOI":"10.3390\/geosciences9070322"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Raghavan, V.S., Kanoulas, D., Laurenzi, A., Caldwell, D.G., and Tsagarakis, N.G. (2019, January 4\u20138). Variable configuration planner for legged-rolling obstacle negotiation locomotion: Application on the centauro robot. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China.","DOI":"10.1109\/IROS40897.2019.8968014"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1002\/rob.21892","article-title":"Fast approximate clearance evaluation for rovers with articulated suspension systems","volume":"37","author":"Otsu","year":"2020","journal-title":"J. Field Robot."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"4048","DOI":"10.1109\/LRA.2021.3065302","article-title":"Virtual Surfaces and Attitude Aware Planning and Behaviours for Negative Obstacle Navigation","volume":"6","author":"Hines","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.jterra.2020.12.001","article-title":"A novel optimal path-planning and following algorithm for wheeled robots on deformable terrains","volume":"96","author":"Taghavifar","year":"2020","journal-title":"J. Terramech."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2010JE003633","article-title":"Spirit Mars Rover Mission: Overview and selected results from the northern Home Plate Winter Haven to the side of Scamander crater","volume":"115","author":"Arvidson","year":"2010","journal-title":"J. Geophys. Res. Planets"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Ishigami, G., Nagatani, K., and Yoshida, K. (2007, January 10\u201314). Path planning for planetary exploration rovers and its evaluation based on wheel slip dynamics. Proceedings of the 2007 IEEE International Conference on Robotics and Automation, Rome, Italy.","DOI":"10.1109\/ROBOT.2007.363672"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MRA.2014.2381359","article-title":"The right path: Comprehensive path planning for lunar exploration rovers","volume":"22","author":"Sutoh","year":"2015","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_67","unstructured":"Inotsume, H., Creager, C., Wettergreen, D., and Whittaker, W. (2016, January 19\u201322). Finding routes for efficient and successful slope ascent for exploration rovers. Proceedings of the 13th International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS), Beijing, China."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1109\/LRA.2020.2975756","article-title":"Robust Path Planning for Slope Traversing under Uncertainty in Slip Prediction","volume":"5","author":"Inotsume","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1177\/0278364920913945","article-title":"The effects of reduced-gravity on planetary rover mobility","volume":"39","author":"Niksirat","year":"2020","journal-title":"Int. J. Robot. Res."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1002\/rob.21459","article-title":"Energy-efficient path planning for solar-powered mobile robots","volume":"30","author":"Plonski","year":"2013","journal-title":"J. Field Robot."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1109\/TASE.2016.2533418","article-title":"Time-optimal path planning with power schedules for a solar-powered ground robot","volume":"14","author":"Kaplan","year":"2016","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Groves, K., Hernandez, E., West, A., Wright, T., and Lennox, B. (2021). Robotic Exploration of an Unknown Nuclear Environment Using Radiation Informed Autonomous Navigation. Robotics, 10.","DOI":"10.3390\/robotics10020078"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Ono, M., Fuchs, T.J., Steffy, A., Maimone, M., and Yen, J. (2015, January 7\u201314). Risk-aware planetary rover operation: Autonomous terrain classification and path planning. Proceedings of the 2015 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2015.7119022"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/MRA.2013.2248309","article-title":"The path to efficiency: Fast marching method for safer, more efficient mobile robot trajectories","volume":"20","author":"Gomez","year":"2013","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_75","unstructured":"Khatib, O. (2015, January 25\u201328). Real-time obstacle avoidance for manipulators and mobile robots. Proceedings of the 1985 IEEE International Conference on Robotics and Automation, St. Louis, MO, USA."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1023\/A:1020564024509","article-title":"Dynamic motion planning for mobile robots using potential field method","volume":"13","author":"Ge","year":"2002","journal-title":"Auton. Robot."},{"key":"ref_77","unstructured":"Vadakkepat, P., Tan, K.C., and Ming-Liang, W. (2000, January 16\u201319). Evolutionary artificial potential fields and their application in real time robot path planning. Proceedings of the 2000 Congress on Evolutionary Computation, CEC00 (Cat. No. 00TH8512), La Jolla, CA, USA."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.robot.2015.06.002","article-title":"New potential field method for rough terrain path planning using genetic algorithm for a 6-wheel rover","volume":"72","author":"Raja","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1016\/j.ijleo.2017.12.169","article-title":"Tangent navigated robot path planning strategy using particle swarm optimized artificial potential field","volume":"158","author":"Zhou","year":"2018","journal-title":"Optik"},{"key":"ref_80","first-page":"3262","article-title":"A novel of repulsive function on artificial potential field for robot path planning","volume":"6","author":"Triharminto","year":"2016","journal-title":"Int. J. Electr. Comput. Eng."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s12555-009-0320-7","article-title":"Escaping route method for a trap situation in local path planning","volume":"7","author":"Kim","year":"2009","journal-title":"Int. J. Control Autom. Syst."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.eswa.2018.01.050","article-title":"Mobile robots path planning: Electrostatic potential field approach","volume":"100","author":"Bayat","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1109\/70.88137","article-title":"The vector field histogram-fast obstacle avoidance for mobile robots","volume":"7","author":"Borenstein","year":"1991","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_84","unstructured":"Ulrich, I., and Borenstein, J. (1998, January 16\u201320). VFH+: Reliable obstacle avoidance for fast mobile robots. Proceedings of the 1998 IEEE International Conference on Robotics and Automation (Cat. No. 98CH36146), Leuven, Belgium."},{"key":"ref_85","unstructured":"Ulrich, I., and Borenstein, J. (2000, January 24\u201328). VFH*: Local Obstacle Avoidance with Lookahead Verification. Proceedings of the 2000 IEEE International Conference on Robotics and Automation (ICRA 2000), San Francisco, CA, USA."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1109\/TAC.1986.1104175","article-title":"Dynamic path planning for a mobile automaton with limited information on the environment","volume":"31","author":"Lumelsky","year":"1986","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_87","first-page":"151","article-title":"A simple local path planning algorithm for autonomous mobile robots","volume":"5","author":"Buniyamin","year":"2011","journal-title":"Int. J. Syst. Appl. Eng. Dev."},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Xu, Q.L., Yu, T., and Bai, J. (2017, January 20\u201322). The mobile robot path planning with motion constraints based on Bug algorithm. Proceedings of the 2017 Chinese Automation Congress (CAC), Jinan, China.","DOI":"10.1109\/CAC.2017.8243168"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1177\/027836499801700706","article-title":"Motion planning in dynamic environments using velocity obstacles","volume":"17","author":"Fiorini","year":"1998","journal-title":"Int. J. Robot. Res."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1109\/JOE.2013.2254214","article-title":"Safe maritime autonomous navigation with COLREGS, using velocity obstacles","volume":"39","author":"Kuwata","year":"2013","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"107793","DOI":"10.1016\/j.oceaneng.2020.107793","article-title":"Global path planning for autonomous ship: A hybrid approach of Fast Marching Square and velocity obstacles methods","volume":"214","author":"Chen","year":"2020","journal-title":"Ocean Eng."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Wilkie, D., Van Den Berg, J., and Manocha, D. (2009, January 10\u201315). Generalized velocity obstacles. Proceedings of the 2009 IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5354175"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/3468.709600","article-title":"Obstacle avoidance in a dynamic environment: A collision cone approach","volume":"28","author":"Chakravarthy","year":"1998","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1109\/TRO.2004.829461","article-title":"A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles","volume":"20","author":"Qu","year":"2004","journal-title":"IEEE Trans. Robot."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/100.580977","article-title":"The dynamic window approach to collision avoidance","volume":"4","author":"Fox","year":"1997","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_96","unstructured":"Brock, O., and Khatib, O. (1999, January 10\u201315). High-speed navigation using the global dynamic window approach. Proceedings of the 1999 IEEE International Conference on Robotics and Automation (Cat. No. 99CH36288C), Detroit, MI, USA."},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Feng, D., Deng, L., Sun, T., Liu, H., Zhang, H., and Zhao, Y. (2020, January 16\u201318). Local Path Planning Based on an Improved Dynamic Window Approach in ROS. Proceedings of the International Conference on Computer Engineering and Networks, Xi\u2019an, China.","DOI":"10.1007\/978-981-15-8462-6_133"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.ifacol.2016.07.610","article-title":"Energy efficient dynamic window approach for local path planning in mobile service robotics","volume":"49","author":"Henkel","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"1729881418754563","DOI":"10.1177\/1729881418754563","article-title":"Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning","volume":"15","author":"Xie","year":"2018","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_100","unstructured":"Quinlan, S., and Khatib, O. (1993, January 2\u20136). Elastic bands: Connecting path planning and control. Proceedings of the IEEE International Conference on Robotics and Automation, Atlanta, GA, USA."},{"key":"ref_101","unstructured":"Khatib, M., Jaouni, H., Chatila, R., and Laumond, J.P. (1997, January 20\u201325). Dynamic path modification for car-like nonholonomic mobile robots. Proceedings of the International Conference on Robotics and Automation, Albuquerque, NM, USA."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"P\u00e9rez, L.H., Aguilar, M.C.M., S\u00e1nchez, N.M., and Montesinos, A.F. (2018). Path Planning Based on Parametric Curves. Adv. Path Plan. Mob. Entities, 125\u2013143.","DOI":"10.5772\/intechopen.72574"},{"key":"ref_103","unstructured":"R\u00f6smann, C., Feiten, W., W\u00f6sch, T., Hoffmann, F., and Bertram, T. (2012, January 21\u201322). Trajectory modification considering dynamic constraints of autonomous robots. Proceedings of the ROBOTIK 2012: 7th German Conference on Robotics, Munich, Germany."},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Mirjalili, S., and Dong, J.S. (2020). Introduction to nature-inspired algorithms. Nature-Inspired Optimizers, Springer.","DOI":"10.1007\/978-3-030-12127-3"},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1007\/s10462-018-09676-2","article-title":"From ants to whales: Metaheuristics for all tastes","volume":"53","author":"Fausto","year":"2020","journal-title":"Artif. Intell. Rev."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/79.543973","article-title":"Genetic algorithms and their applications","volume":"13","author":"Tang","year":"1996","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1177\/105971239400200303","article-title":"Using genetic algorithms to learn reactive control parameters for autonomous robotic navigation","volume":"2","author":"Ram","year":"1994","journal-title":"Adapt. Behav."},{"key":"ref_108","unstructured":"Han, W.G., Baek, S.M., and Kuc, T.Y. (1997, January 12\u201315). Genetic algorithm based path planning and dynamic obstacle avoidance of mobile robots. Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, Orlando, FL, USA."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1564","DOI":"10.1016\/j.compeleceng.2012.06.016","article-title":"Dynamic path planning of mobile robots with improved genetic algorithm","volume":"38","author":"Tuncer","year":"2012","journal-title":"Comput. Electr. Eng."},{"key":"ref_110","doi-asserted-by":"crossref","unstructured":"Alajlan, M., Koubaa, A., Chaari, I., Bennaceur, H., and Ammar, A. (2013, January 15\u201317). Global path planning for mobile robots in large-scale grid environments using genetic algorithms. Proceedings of the 2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR), Sousse, Tunisia.","DOI":"10.1109\/ICBR.2013.6729271"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.robot.2016.12.008","article-title":"Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control","volume":"89","author":"Bakdi","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Lee, H.Y., Shin, H., and Chae, J. (2018). Path planning for mobile agents using a genetic algorithm with a direction guided factor. Electronics, 7.","DOI":"10.3390\/electronics7100212"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.jocs.2017.08.004","article-title":"Bezier curve based path planning in a dynamic field using modified genetic algorithm","volume":"25","author":"Elhoseny","year":"2018","journal-title":"J. Comput. Sci."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.procs.2018.01.113","article-title":"Genetic algorithm based approach for autonomous mobile robot path planning","volume":"127","author":"Lamini","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.neucom.2012.09.019","article-title":"Robot path planning in uncertain environment using multi-objective particle swarm optimization","volume":"103","author":"Zhang","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_116","doi-asserted-by":"crossref","unstructured":"Lu, L., and Gong, D. (2008, January 18\u201320). Robot path planning in unknown environments using particle swarm optimization. Proceedings of the 2008 Fourth International Conference on Natural Computation, Washington, DC, USA.","DOI":"10.1109\/ICNC.2008.923"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.asoc.2017.05.012","article-title":"A hierarchical global path planning approach for mobile robots based on multi-objective particle swarm optimization","volume":"59","author":"Mac","year":"2017","journal-title":"Appl. Soft Comput."},{"key":"ref_118","unstructured":"Cong, Y.Z., and Ponnambalam, S. (2009, January 14\u201317). Mobile robot path planning using ant colony optimization. Proceedings of the 2009 IEEE\/ASME International Conference on Advanced Intelligent Mechatronics, Singapore."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"63419","DOI":"10.4236\/jcc.2016.42002","article-title":"Robot global path planning based on an improved ant colony algorithm","volume":"4","author":"Cao","year":"2016","journal-title":"J. Comput. Commun."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1007\/s11771-006-0018-4","article-title":"Global path planning approach based on ant colony optimization algorithm","volume":"13","author":"Wen","year":"2006","journal-title":"J. Cent. South Univ. Technol."},{"key":"ref_121","first-page":"329","article-title":"A chaotic ant colony system for path planning of mobile robot","volume":"9","author":"You","year":"2016","journal-title":"Int. J. Hybrid Inf. Technol."},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Che, H., Wu, Z., Kang, R., and Yun, C. (2016, January 20\u201322). Global path planning for explosion-proof robot based on improved ant colony optimization. Proceedings of the 2016 Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Tokyo, Japan.","DOI":"10.1109\/ACIRS.2016.7556184"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1007\/s00521-019-04172-2","article-title":"Research on path planning of mobile robot based on improved ant colony algorithm","volume":"32","author":"Luo","year":"2020","journal-title":"Neural Comput. Appl."},{"key":"ref_124","doi-asserted-by":"crossref","unstructured":"Wang, L., Kan, J., Guo, J., and Wang, C. (2019). 3D path planning for the ground robot with improved ant colony optimization. Sensors, 19.","DOI":"10.3390\/s19040815"},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"4749","DOI":"10.1007\/s00500-020-05483-6","article-title":"Energy-efficient green ant colony optimization for path planning in dynamic 3D environments","volume":"25","author":"Sangeetha","year":"2021","journal-title":"Soft Comput."},{"key":"ref_126","doi-asserted-by":"crossref","unstructured":"Sangeetha, V., Krishankumar, R., Ravichandran, K.S., Cavallaro, F., Kar, S., Pamucar, D., and Mardani, A. (2021). A Fuzzy Gain-Based Dynamic Ant Colony Optimization for Path Planning in Dynamic Environments. Symmetry, 13.","DOI":"10.3390\/sym13020280"},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1016\/j.procs.2018.07.064","article-title":"Optimal path planning of mobile robot using hybrid cuckoo search-bat algorithm","volume":"133","author":"Saraswathi","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"4745","DOI":"10.1007\/s10586-018-2360-3","article-title":"Intelligent B\u00e9zier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm","volume":"22","author":"Tharwat","year":"2019","journal-title":"Clust. Comput."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.dt.2018.06.004","article-title":"Path planning in uncertain environment by using firefly algorithm","volume":"14","author":"Patle","year":"2018","journal-title":"Def. Technol."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"397","DOI":"10.2507\/IJSIMM18(3)474","article-title":"Optimal path planning for an autonomous mobile robot using dragonfly algorithm","volume":"18","author":"Muthukumaran","year":"2019","journal-title":"Int. J. Simul. Model."},{"key":"ref_131","doi-asserted-by":"crossref","unstructured":"Elmi, Z., and Efe, M.\u00d6. (2018, January 20\u201322). Multi-objective grasshopper optimization algorithm for robot path planning in static environments. Proceedings of the 2018 IEEE International Conference on Industrial Technology (ICIT), Lyon, France.","DOI":"10.1109\/ICIT.2018.8352184"},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1080\/0952813X.2020.1764631","article-title":"Online path planning of mobile robot using grasshopper algorithm in a dynamic and unknown environment","volume":"33","author":"Elmi","year":"2020","journal-title":"J. Exp. Theor. Artif. Intell."},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Tsai, P.W., and Dao, T.K. (2016, January 7\u20139). Robot path planning optimization based on multiobjective grey wolf optimizer. Proceedings of the International Conference on Genetic and Evolutionary Computing, Fuzhou, China.","DOI":"10.1007\/978-3-319-48490-7_20"},{"key":"ref_134","unstructured":"Do\u011fan, L., and Y\u00fczge\u00e7, U. (2018, January 11\u201313). Robot Path Planning using Gray Wolf Optimizer. Proceedings of the International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES\u201918), Safranbolu, Turkey."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The whale optimization algorithm","volume":"95","author":"Mirjalili","year":"2016","journal-title":"Adv. Eng. Softw."},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Dao, T.K., Pan, T.S., and Pan, J.S. (2016, January 6\u201310). A multi-objective optimal mobile robot path planning based on whale optimization algorithm. Proceedings of the 2016 IEEE 13th International Conference on Signal Processing (ICSP), Chengdu, China.","DOI":"10.1109\/ICSP.2016.7877851"},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Mohanty, P.K., and Parhi, D.R. (2013, January 19\u201321). Cuckoo search algorithm for the mobile robot navigation. Proceedings of the International Conference on Swarm, Evolutionary, and Memetic Computing, Chennai, India.","DOI":"10.1007\/978-3-319-03753-0_47"},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1049\/iet-smt.2016.0273","article-title":"Analysis of FPA and BA meta-heuristic controllers for optimal path planning of mobile robot in cluttered environment","volume":"11","author":"Ghosh","year":"2017","journal-title":"IET Sci. Meas. Technol."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.robot.2014.07.002","article-title":"Autonomous robot path planning in dynamic environment using a new optimization technique inspired by bacterial foraging technique","volume":"64","author":"Hossain","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1109\/TRA.2002.1019461","article-title":"Behavior-based robot navigation on challenging terrain: A fuzzy logic approach","volume":"18","author":"Seraji","year":"2002","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1080\/0232929032000115100","article-title":"Motion control for mobile robot obstacle avoidance and navigation: A fuzzy logic-based approach","volume":"43","author":"Zavlangas","year":"2003","journal-title":"Syst. Anal. Model. Simul."},{"key":"ref_142","unstructured":"Wang, M. (2005, January 18\u201321). Fuzzy logic based robot path planning in unknown environment. Proceedings of the 2005 International Conference on Machine Learning and Cybernetics, Guangzhou, China."},{"key":"ref_143","doi-asserted-by":"crossref","unstructured":"Pandey, A., Sonkar, R.K., Pandey, K.K., and Parhi, D. (2014, January 10\u201311). Path planning navigation of mobile robot with obstacles avoidance using fuzzy logic controller. Proceedings of the 2014 IEEE 8th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, India.","DOI":"10.1109\/ISCO.2014.7103914"},{"key":"ref_144","doi-asserted-by":"crossref","unstructured":"Yan, Y., and Li, Y. (2016, January 12\u201315). Mobile robot autonomous path planning based on fuzzy logic and filter smoothing in dynamic environment. Proceedings of the 2016 12th World Congress on Intelligent Control and Automation (WCICA), Guilin, China.","DOI":"10.1109\/WCICA.2016.7578767"},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.dt.2017.01.001","article-title":"Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm","volume":"13","author":"Pandey","year":"2017","journal-title":"Def. Technol."},{"key":"ref_146","unstructured":"Zou, A.M., Hou, Z.G., Fu, S.Y., and Tan, M. (June, January 28). Neural networks for mobile robot navigation: A survey. Proceedings of the International Symposium on Neural Networks, Chengdu, China."},{"key":"ref_147","doi-asserted-by":"crossref","unstructured":"Engedy, I., and Horv\u00e1th, G. (2010, January 18\u201320). Artificial neural network based local motion planning of a wheeled mobile robot. Proceedings of the 2010 11th International Symposium on Computational Intelligence and Informatics (CINTI), Budapest, Hungary.","DOI":"10.1109\/CINTI.2010.5672245"},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1007\/s11071-017-3553-7","article-title":"A type of biased consensus-based distributed neural network for path planning","volume":"89","author":"Zhang","year":"2017","journal-title":"Nonlinear Dyn."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0168-1699(97)00029-X","article-title":"Path planning of an agricultural mobile robot by neural network and genetic algorithm","volume":"18","author":"Noguchi","year":"1997","journal-title":"Comput. Electron. Agric."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1631\/jzus.2005.A0549","article-title":"Neural network and genetic algorithm based global path planning in a static environment","volume":"6","author":"Xin","year":"2005","journal-title":"J. Zhejiang Univ.-Sci. A"},{"key":"ref_151","doi-asserted-by":"crossref","unstructured":"Zhu, A., and Yang, S.X. (2009). An adaptive neuro-fuzzy controller for robot navigation. Recent Advances in Intelligent Control Systems, Springer.","DOI":"10.1007\/978-1-84882-548-2_12"},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1080\/10798587.2009.10643032","article-title":"A fuzzy-neural network approach to multisensor integration for obstacle avoidance of a mobile robot","volume":"15","author":"Shi","year":"2009","journal-title":"Intell. Autom. Soft Comput."},{"key":"ref_153","first-page":"128","article-title":"Reactive navigation of autonomous mobile robot using neuro-fuzzy system","volume":"2","author":"Joshi","year":"2011","journal-title":"Int. J. Robot. Autom. (IJRA)"},{"key":"ref_154","doi-asserted-by":"crossref","unstructured":"Wang, H., Duan, J., Wang, M., Zhao, J., and Dong, Z. (2018, January 12\u201314). Research on robot path planning based on fuzzy neural network algorithm. Proceedings of the 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China.","DOI":"10.1109\/IAEAC.2018.8577599"},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"2527","DOI":"10.12785\/amis\/080551","article-title":"A new intelligent motion planning for mobile robot navigation using multiple adaptive neuro-fuzzy inference system","volume":"8","author":"Mohanty","year":"2014","journal-title":"Appl. Math. Inf. Sci."},{"key":"ref_156","doi-asserted-by":"crossref","unstructured":"Blum, T., Jones, W., and Yoshida, K. (2020, January 19\u201321). PPMC training algorithm: A deep learning based path planner and motion controller. Proceedings of the 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), Fukuoka, Japan.","DOI":"10.1109\/ICAIIC48513.2020.9065237"},{"key":"ref_157","doi-asserted-by":"crossref","unstructured":"Yu, X., Wang, P., and Zhang, Z. (2021). Learning-Based End-to-End Path Planning for Lunar Rovers with Safety Constraints. Sensors, 21.","DOI":"10.3390\/s21030796"},{"key":"ref_158","doi-asserted-by":"crossref","unstructured":"Faust, A., Oslund, K., Ramirez, O., Francis, A., Tapia, L., Fiser, M., and Davidson, J. (2018, January 21\u201326). PRM-RL: Long-range robotic navigation tasks by combining reinforcement learning and sampling-based planning. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8461096"},{"key":"ref_159","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A note on two problems in connexion with graphs","volume":"1","author":"Dijkstra","year":"1959","journal-title":"Numer. Math."},{"key":"ref_160","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TSSC.1968.300136","article-title":"A formal basis for the heuristic determination of minimum cost paths","volume":"4","author":"Hart","year":"1968","journal-title":"IEEE Trans. Syst. Sci. Cybern."},{"key":"ref_161","unstructured":"Stentz, A. (1994, January 8\u201313). Optimal and efficient path planning for partially-known environments. Proceedings of the 1994 IEEE International Conference on Robotics and Automation (ICRA), San Diego, CA, USA."},{"key":"ref_162","unstructured":"Stentz, A. (1995, January 20\u201325). The focussed d* algorithm for real-time replanning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Montreal, QC, Canada."},{"key":"ref_163","unstructured":"Koenig, S., and Likhachev, M. (2002, January 9\u201314). Incremental A*. Proceedings of the Advances in Neural Information Processing Systems, Vancouver, BC, Canada."},{"key":"ref_164","unstructured":"Koenig, S., and Likhachev, M. (August, January 28). D* Lite. Proceedings of the AAAI\/IAAI 2002, Edmonton, AB, Canada."},{"key":"ref_165","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.artint.2003.12.001","article-title":"Lifelong planning A*","volume":"155","author":"Koenig","year":"2004","journal-title":"Artif. Intell."},{"key":"ref_166","doi-asserted-by":"crossref","unstructured":"Colas, F., Mahesh, S., Pomerleau, F., Liu, M., and Siegwart, R. (2013, January 3\u20137). 3d path planning and execution for search and rescue ground robots. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696431"},{"key":"ref_167","doi-asserted-by":"crossref","first-page":"1613","DOI":"10.1016\/j.artint.2007.11.009","article-title":"Anytime search in dynamic graphs","volume":"172","author":"Likhachev","year":"2008","journal-title":"Artif. Intell."},{"key":"ref_168","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1177\/0278364909359210","article-title":"Path planning for autonomous vehicles in unknown semi-structured environments","volume":"29","author":"Dolgov","year":"2010","journal-title":"Int. J. Robot. Res."},{"key":"ref_169","unstructured":"Ferguson, D., and Stentz, A. (2005). The Field D* Algorithm for Improved Path Planning and Replanning in Uniform and Non-Uniform Cost Environments, Robotics Institute, Carnegie Mellon University. Technical Report CMU-RI-TR-05-19."},{"key":"ref_170","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/rob.20287","article-title":"Global planning on the Mars Exploration Rovers: Software integration and surface testing","volume":"26","author":"Carsten","year":"2009","journal-title":"J. Field Robot."},{"key":"ref_171","unstructured":"Nash, A., Daniel, K., Koenig, S., and Felner, A. (2007, January 22\u201326). Theta*: Any-angle path planning on grids. Proceedings of the AAAI Conference on Artificial Intelligence, Vancouver, BC, Canada."},{"key":"ref_172","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1613\/jair.2994","article-title":"Theta*: Any-angle path planning on grids","volume":"39","author":"Daniel","year":"2010","journal-title":"J. Artif. Intell. Res."},{"key":"ref_173","unstructured":"Nash, A., Koenig, S., and Likhachev, M. (2009, January 12\u201317). Incremental Phi*: Incremental any-angle path planning on grids. Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, Pasadena, CA, USA."},{"key":"ref_174","doi-asserted-by":"crossref","unstructured":"Nash, A., Koenig, S., and Tovey, C. (2010, January 11\u201315). Lazy Theta*: Any-angle path planning and path length analysis in 3D. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, Atlanta, GA, USA.","DOI":"10.1609\/aaai.v24i1.7566"},{"key":"ref_175","doi-asserted-by":"crossref","unstructured":"Choi, S., and Yu, W. (2011, January 9\u201313). Any-angle path planning on non-uniform costmaps. Proceedings of the 2011 IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5979769"},{"key":"ref_176","unstructured":"\u0160i\u0161l\u00e1k, D., Volf, P., and Pechoucek, M. (2009, January 19\u201323). Accelerated A* trajectory planning: Grid-based path planning comparison. Proceedings of the 19th International Conference on Automated Planning & Scheduling (ICAPS), Thessaloniki, Greece."},{"key":"ref_177","doi-asserted-by":"crossref","unstructured":"Yap, P., Burch, N., Holte, R.C., and Schaeffer, J. (2011, January 7\u201311). Block A*: Database-driven search with applications in any-angle path-planning. Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, San Francisco, CA, USA.","DOI":"10.1609\/aaai.v25i1.7813"},{"key":"ref_178","doi-asserted-by":"crossref","unstructured":"Yap, P.K.Y., Burch, N., Holte, R.C., and Schaeffer, J. (2011, January 11\u201314). Any-angle path planning for computer games. Proceedings of the Seventh Artificial Intelligence and Interactive Digital Entertainment Conference, Palo Alto, CA, USA.","DOI":"10.1609\/aiide.v7i1.12445"},{"key":"ref_179","doi-asserted-by":"crossref","unstructured":"Mu\u00f1oz, P., and R-Moreno, M.D. (2012). S-Theta: Low steering path-planning algorithm. Research and Development in Intelligent Systems XXIX, Springer.","DOI":"10.1007\/978-1-4471-4739-8_8"},{"key":"ref_180","unstructured":"Mu\u00f1oz, P., R-Moreno, M.D., and Casta\u00f1o, B. (2016, January 13\u201315). 3Dana: Path Planning on 3D Surfaces. Proceedings of the Thirty-Sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK."},{"key":"ref_181","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.engappai.2017.02.010","article-title":"3Dana: A path planning algorithm for surface robotics","volume":"60","year":"2017","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_182","doi-asserted-by":"crossref","unstructured":"Uras, T., and Koenig, S. (2015, January 7\u201311). Speeding-up any-angle path-planning on grids. Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling, Jerusalem, Israel.","DOI":"10.1609\/icaps.v25i1.13724"},{"key":"ref_183","unstructured":"Uras, T., and Koenig, S. (2015, January 11\u201313). An empirical comparison of any-angle path-planning algorithms. Proceedings of the Eighth Annual Symposium on Combinatorial Search, Ein Gedi, the Dead Sea, Israel."},{"key":"ref_184","doi-asserted-by":"crossref","unstructured":"Harabor, D.D., and Grastien, A. (2013, January 10\u201314). An optimal any-angle pathfinding algorithm. Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling, Rome, Italy.","DOI":"10.1609\/icaps.v23i1.13609"},{"key":"ref_185","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1613\/jair.5007","article-title":"Optimal any-angle pathfinding in practice","volume":"56","author":"Harabor","year":"2016","journal-title":"J. Artif. Intell. Res."},{"key":"ref_186","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1177\/0278364911406761","article-title":"Sampling-based algorithms for optimal motion planning","volume":"30","author":"Karaman","year":"2011","journal-title":"Int. J. Robot. Res."},{"key":"ref_187","doi-asserted-by":"crossref","unstructured":"LaValle, S.M. (2006). Planning Algorithms, Cambridge University Press.","DOI":"10.1017\/CBO9780511546877"},{"key":"ref_188","unstructured":"Kuffner, J.J., and LaValle, S.M. (2000, January 24\u201328). RRT-connect: An efficient approach to single-query path planning. Proceedings of the 2000 ICRA, Millennium Conference, IEEE International Conference on Robotics and Automation, Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA."},{"key":"ref_189","unstructured":"Yershova, A., Jaillet, L., Sim\u00e9on, T., and LaValle, S.M. (2005, January 18\u201322). Dynamic-domain RRTs: Efficient exploration by controlling the sampling domain. Proceedings of the 2005 IEEE International Conference on Robotics and Automation (ICRA), Barcelona, Spain."},{"key":"ref_190","doi-asserted-by":"crossref","unstructured":"Arslan, O., and Tsiotras, P. (2013, January 6\u201310). Use of relaxation methods in sampling-based algorithms for optimal motion planning. Proceedings of the 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630906"},{"key":"ref_191","doi-asserted-by":"crossref","unstructured":"Gammell, J.D., Srinivasa, S.S., and Barfoot, T.D. (2014, January 14\u201318). Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942976"},{"key":"ref_192","doi-asserted-by":"crossref","unstructured":"Gammell, J.D., Srinivasa, S.S., and Barfoot, T.D. (2015, January 25\u201330). Batch informed trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139620"},{"key":"ref_193","doi-asserted-by":"crossref","unstructured":"Choudhury, S., Gammell, J.D., Barfoot, T.D., Srinivasa, S.S., and Scherer, S. (2016, January 16\u201320). Regionally accelerated batch informed trees (rabit*): A framework to integrate local information into optimal path planning. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487615"},{"key":"ref_194","doi-asserted-by":"crossref","unstructured":"Strub, M.P., and Gammell, J.D. (August, January 31). Adaptively Informed Trees (AIT*): Fast asymptotically optimal path planning through adaptive heuristics. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Virtual.","DOI":"10.1109\/ICRA40945.2020.9197338"},{"key":"ref_195","doi-asserted-by":"crossref","unstructured":"Strub, M.P., and Gammell, J.D. (August, January 31). Advanced BIT*(ABIT*): Sampling-based planning with advanced graph-search techniques. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Virtual.","DOI":"10.1109\/ICRA40945.2020.9196580"},{"key":"ref_196","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1109\/70.508439","article-title":"Probabilistic roadmaps for path planning in high-dimensional configuration spaces","volume":"12","author":"Kavraki","year":"1996","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_197","doi-asserted-by":"crossref","first-page":"458","DOI":"10.4218\/etrij.2018-0041","article-title":"Incremental hierarchical roadmap construction for efficient path planning","volume":"40","author":"Park","year":"2018","journal-title":"ETRI J."},{"key":"ref_198","doi-asserted-by":"crossref","unstructured":"Ichter, B., Schmerling, E., Lee, T.W.E., and Faust, A. (August, January 31). Learned critical probabilistic roadmaps for robotic motion planning. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Virtual.","DOI":"10.1109\/ICRA40945.2020.9197106"},{"key":"ref_199","doi-asserted-by":"crossref","unstructured":"Ichter, B., Schmerling, E., and Pavone, M. (2017, January 10\u201312). Group Marching Tree: Sampling-based approximately optimal motion planning on GPUs. Proceedings of the 2017 First IEEE International Conference on Robotic Computing (IRC), Taichung, Taiwan.","DOI":"10.1109\/IRC.2017.72"},{"key":"ref_200","doi-asserted-by":"crossref","unstructured":"Dunlap, D.D., Caldwell, C.V., and Collins, E.G. (2010, January 8\u201310). Nonlinear model predictive control using sampling and goal-directed optimization. Proceedings of the 2010 IEEE International Conference on Control Applications, Yokohama, Japan.","DOI":"10.1109\/CCA.2010.5611171"},{"key":"ref_201","doi-asserted-by":"crossref","first-page":"7821942","DOI":"10.1155\/2020\/7821942","article-title":"Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot","volume":"2020","author":"Wang","year":"2020","journal-title":"Discret. Dyn. Nat. Soc."},{"key":"ref_202","doi-asserted-by":"crossref","unstructured":"Tonon, D., Aronna, M.S., and Kalise, D. (2017). Optimal Control: Novel Directions and Applications, Springer.","DOI":"10.1007\/978-3-319-60771-9"},{"key":"ref_203","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1126\/science.153.3731.34","article-title":"Dynamic programming","volume":"153","author":"Bellman","year":"1966","journal-title":"Science"},{"key":"ref_204","doi-asserted-by":"crossref","unstructured":"Festa, A., Guglielmi, R., Hermosilla, C., Picarelli, A., Sahu, S., Sassi, A., and Silva, F.J. (2017). Hamilton\u2013Jacobi\u2013Bellman Equations. Optimal Control: Novel Directions and Applications, Springer International Publishing.","DOI":"10.1007\/978-3-319-60771-9_2"},{"key":"ref_205","unstructured":"Sethian, J.A. (1999). Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science, Cambridge University Press."},{"key":"ref_206","unstructured":"Chiang, C.H., Chiang, P.J., Fei, J.C.C., and Liu, J.S. (2007, January 9\u201311). A comparative study of implementing Fast Marching Method and A* SEARCH for mobile robot path planning in grid environment: Effect of map resolution. Proceedings of the 2007 IEEE Workshop on Advanced Robotics and Its Social Impacts, Hsinchu, Taiwan."},{"key":"ref_207","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1023\/A:1011234012449","article-title":"Optimal algorithm for shape from shading and path planning","volume":"14","author":"Kimmel","year":"2001","journal-title":"J. Math. Imaging Vis."},{"key":"ref_208","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.robot.2012.10.012","article-title":"Application of the fast marching method for outdoor motion planning in robotics","volume":"61","author":"Garrido","year":"2013","journal-title":"Robot. Auton. Syst."},{"key":"ref_209","doi-asserted-by":"crossref","unstructured":"Garrido, S., \u00c1lvarez, D., and Moreno, L. (2015, January 19\u201321). Path Planning for Mars Rovers Using the Fast Marching Method. Proceedings of the Robot 2015: Second Iberian Robotics Conference, Lisbon, Portugal.","DOI":"10.1007\/978-3-319-27146-0_8"},{"key":"ref_210","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1002\/acs.2561","article-title":"Predictive navigation of unmanned surface vehicles in a dynamic maritime environment when using the fast marching method","volume":"31","author":"Liu","year":"2017","journal-title":"Int. J. Adapt. Control Signal Process."},{"key":"ref_211","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/j.apor.2016.06.013","article-title":"The angle guidance path planning algorithms for unmanned surface vehicle formations by using the fast marching method","volume":"59","author":"Liu","year":"2016","journal-title":"Appl. Ocean Res."},{"key":"ref_212","unstructured":"Philippsen, R. (November, January 29). E* Interpolated Graph Replanner. Proceedings of the Workshop Proceedings on Algorithmic Motion Planning for Autonomous Robots in Challenging Environments, Held in Conjunction with the IEEE International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, USA."},{"key":"ref_213","unstructured":"Philippsen, R., Kolski, S., Macek, K., and Jensen, B. (2008, January 19\u201323). Mobile robot planning in dynamic environments and on growable costmaps. Proceedings of the 2008 IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA."},{"key":"ref_214","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s10846-012-9794-2","article-title":"Fast path re-planning based on fast marching and level sets","volume":"71","author":"Xu","year":"2013","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_215","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1137\/S0036142901392742","article-title":"Ordered upwind methods for static Hamilton\u2013Jacobi equations: Theory and algorithms","volume":"41","author":"Sethian","year":"2003","journal-title":"SIAM J. Numer. Anal."},{"key":"ref_216","doi-asserted-by":"crossref","first-page":"5256","DOI":"10.1109\/ACCESS.2019.2963368","article-title":"Fast Marching Based Path Generating Algorithm in Anisotropic Environment with Perturbations","volume":"8","author":"Xu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_217","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1007\/s10915-016-0163-3","article-title":"Convergence rate for the ordered upwind method","volume":"68","author":"Shum","year":"2016","journal-title":"J. Sci. Comput."},{"key":"ref_218","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1137\/S0036142902419600","article-title":"Fast sweeping methods for static Hamilton\u2013Jacobi equations","volume":"42","author":"Kao","year":"2005","journal-title":"SIAM J. Numer. Anal."},{"key":"ref_219","doi-asserted-by":"crossref","first-page":"2853","DOI":"10.1137\/090749645","article-title":"Some improvements for the fast sweeping method","volume":"32","author":"Bak","year":"2010","journal-title":"SIAM J. Sci. Comput."},{"key":"ref_220","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.jcp.2012.11.042","article-title":"A parallel fast sweeping method for the Eikonal equation","volume":"237","author":"Detrixhe","year":"2013","journal-title":"J. Comput. Phys."},{"key":"ref_221","doi-asserted-by":"crossref","first-page":"2512","DOI":"10.1137\/060670298","article-title":"A fast iterative method for eikonal equations","volume":"30","author":"Jeong","year":"2008","journal-title":"SIAM J. Sci. Comput."},{"key":"ref_222","doi-asserted-by":"crossref","unstructured":"Ratliff, N., Zucker, M., Bagnell, J.A., and Srinivasa, S. (2009, January 12\u201317). CHOMP: Gradient optimization techniques for efficient motion planning. Proceedings of the 2009 IEEE International Conference on Robotics and Automation (ICRA), Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152817"},{"key":"ref_223","doi-asserted-by":"crossref","unstructured":"Van Den Berg, J., Patil, S., and Alterovitz, R. (2017). Motion planning under uncertainty using differential dynamic programming in belief space. Robotics Research, Springer.","DOI":"10.1007\/978-3-319-29363-9_27"},{"key":"ref_224","doi-asserted-by":"crossref","unstructured":"Ajanovi\u0107, Z., Stolz, M., and Horn, M. (2018). Energy-efficient driving in dynamic environment: Globally optimal MPC-like motion planning framework. Advanced Microsystems for Automotive Applications 2017, Springer.","DOI":"10.1007\/978-3-319-66972-4_10"},{"key":"ref_225","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.robot.2003.10.003","article-title":"Near-optimal dynamic trajectory generation and control of an omnidirectional vehicle","volume":"46","author":"Ganguly","year":"2004","journal-title":"Robot. Auton. Syst."},{"key":"ref_226","doi-asserted-by":"crossref","unstructured":"Ma, C.S., and Miller, R.H. (2006, January 14\u201316). MILP optimal path planning for real-time applications. Proceedings of the 2006 American Control Conference, Minneapolis, MN, USA.","DOI":"10.1109\/ACC.2006.1657504"},{"key":"ref_227","unstructured":"Kogan, D., and Murray, R. (2006, January 13\u201315). Optimization-based navigation for the DARPA Grand Challenge. Proceedings of the 45th Conference on Decision and Control (CDC), San Diego, CA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/7898\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T13:17:38Z","timestamp":1736255858000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/23\/7898"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,26]]},"references-count":227,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21237898"],"URL":"https:\/\/doi.org\/10.3390\/s21237898","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2021,11,26]]}}}