{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:49:58Z","timestamp":1740149398846,"version":"3.37.3"},"reference-count":79,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T00:00:00Z","timestamp":1597104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1239243"],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfortunately, current disaster robots usually lack the maneuverability to efficiently traverse these areas, which often necessitate extreme navigational capabilities, such as centimeter-scale clearance. Recent work has shown that it is possible to control the locomotion of insects such as the Madagascar hissing cockroach (Gromphadorhina portentosa) through bioelectrical stimulation of their neuro-mechanical system. This provides access to a novel agent that can traverse areas that are inaccessible to traditional robots. In this paper, we present a data-driven inertial navigation system that is capable of localizing cockroaches in areas where GPS is not available. We pose the navigation problem as a two-point boundary-value problem where the goal is to reconstruct a cockroach\u2019s trajectory between the starting and ending states, which are assumed to be known. We validated our technique using nine trials that were conducted in a circular arena using a biobotic agent equipped with a thorax-mounted, low-cost inertial measurement unit. Results show that we can achieve centimeter-level accuracy. This is accomplished by estimating the cockroach\u2019s velocity\u2014using regression models that have been trained to estimate the speed and heading from the inertial signals themselves\u2014and solving an optimization problem so that the boundary-value constraints are satisfied.<\/jats:p>","DOI":"10.3390\/s20164486","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T13:28:57Z","timestamp":1597152537000},"page":"4486","source":"Crossref","is-referenced-by-count":10,"title":["Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6732-3459","authenticated-orcid":false,"given":"Jeremy","family":"Cole","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, NC State University, Raleigh, NC 27695, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5538-262X","authenticated-orcid":false,"given":"Alper","family":"Bozkurt","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, NC State University, Raleigh, NC 27695, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4056-8309","authenticated-orcid":false,"given":"Edgar","family":"Lobaton","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, NC State University, Raleigh, NC 27695, USA"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Murphy, R.R., Tadokoro, S., and Kleiner, A. (2016). Disaster robotics. Springer Handbook of Robotics, Springer.","DOI":"10.1007\/978-3-319-32552-1_60"},{"key":"ref_2","unstructured":"United Nations Department of Public Information (2020, August 09). 2018 Revision of World Urbanization Prospects Press Release. Available online: https:\/\/population.un.org\/wup\/Publications\/Files\/WUP2018-PressRelease.pdf."},{"key":"ref_3","unstructured":"Force, B. (2011). Texas Task Force 1: Urban Search and Rescue, Texas A&M University Press."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/MRA.2004.1337826","article-title":"Trial by fire [rescue robots]","volume":"11","author":"Murphy","year":"2004","journal-title":"IEEE Robot. Autom. Magaz."},{"key":"ref_5","unstructured":"International Atomic Energy Agency (2015). The Fukushima Daiichi Accident, IAEA."},{"key":"ref_6","unstructured":"McKinney, R., Crocco, W., Stricklin, K.G., Murray, K.A., Blankenship, S.T., Davidson, R.D., Urosek, J.E., Stephan, C.R., and Beiter, D.A. (2002). Report of Investigation: Fatal Underground Coal Mine Explosions, September 23, 2001, no. 5 Mine, United States Department of Labor\u2014Mine Safety and Health Administration. Technical Report."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"492","DOI":"10.3109\/10408444.2015.1044601","article-title":"Health effects of World Trade Center (WTC) Dust: An unprecedented disaster with inadequate risk management","volume":"45","author":"Lippmann","year":"2015","journal-title":"Crit. Rev. Toxicol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Murphy, R.R. (2014). Disaster Robotics, MIT Press.","DOI":"10.7551\/mitpress\/9407.001.0001"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Iida, F., and Ijspeert, A.J. (2016). Biologically inspired robotics. Springer Handbook of Robotics, Springer.","DOI":"10.1007\/978-3-319-32552-1_75"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1177\/02783640122067570","article-title":"RHex: A simple and highly mobile hexapod robot","volume":"20","author":"Saranli","year":"2001","journal-title":"Int. J. Robot. Res."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Haldane, D.W., Peterson, K.C., Bermudez, F.L.G., and Fearing, R.S. (2013, January 6\u201310). Animal-inspired design and aerodynamic stabilization of a hexapedal millirobot. Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6631034"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hatazaki, K., Konyo, M., Isaki, K., Tadokoro, S., and Takemura, F. (November, January 20). Active scope camera for urban search and rescue. Proceedings of the IROS 2007 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA.","DOI":"10.1109\/IROS.2007.4399386"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1109\/LRA.2018.2792688","article-title":"A Soft Robotic Gripper with Gecko-Inspired Adhesive","volume":"3","author":"Glick","year":"2018","journal-title":"IEEE Robot. Automat. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Hawkes, E.W., Ulmen, J., Esparza, N., and Cutkosky, M.R. (2011, January 25\u201330). Scaling walls: Applying dry adhesives to the real world. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6048866"},{"key":"ref_15","unstructured":"Latif, T. (2016). Tissue-Electrode Interface Characterization for Optimization of Biobotic Control of Roach-bots. [Ph.D. Thesis, North Carolina State University]."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Latif, T., and Bozkurt, A. (September, January 28). Line following terrestrial insect biobots. Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), San Diego, CA, USA.","DOI":"10.1109\/EMBC.2012.6346095"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Dirafzoon, A., Latif, T., Gong, F., Sichitiu, M., Bozkurt, A., and Lobaton, E. (2017, January 5\u20139). Biobotic motion and behavior analysis in response to directional neurostimulation. Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA.","DOI":"10.1109\/ICASSP.2017.7952598"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1673\/031.010.4001","article-title":"Foot morphology and substrate adhesion in the Madagascan hissing cockroach, Gromphadorhina portentosa","volume":"10","author":"Codd","year":"2010","journal-title":"J. Insect Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"E950","DOI":"10.1073\/pnas.1514591113","article-title":"Cockroaches traverse crevices, crawl rapidly in confined spaces, and inspire a soft, legged robot","volume":"113","author":"Jayaram","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1109\/MC.2016.136","article-title":"A biobotic distributed sensor network for under-rubble search and rescue","volume":"49","author":"Bozkurt","year":"2016","journal-title":"Computer"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/MPUL.2017.2729413","article-title":"Roach Biobots: Toward Reliability and Optimization of Control","volume":"8","author":"Latif","year":"2017","journal-title":"IEEE Pulse"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.robot.2016.11.004","article-title":"A framework for mapping with biobotic insect networks: From local to global maps","volume":"88","author":"Dirafzoon","year":"2017","journal-title":"Robot. Autonom. Syst."},{"key":"ref_23","unstructured":"Groves, P.D. (2013). Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems, Artech House. [2nd ed.]."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1109\/MRA.2011.943233","article-title":"Visual odometry [tutorial]","volume":"18","author":"Scaramuzza","year":"2011","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Bloesch, M., Omari, S., Hutter, M., and Siegwart, R. (October, January 28). Robust visual inertial odometry using a direct EKF-based approach. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots And Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7353389"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1177\/0278364913481251","article-title":"High-precision, consistent EKF-based visual-inertial odometry","volume":"32","author":"Li","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1177\/0278364914554813","article-title":"Keyframe-based visual\u2013inertial odometry using nonlinear optimization","volume":"34","author":"Leutenegger","year":"2015","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wooden, D., Malchano, M., Blankespoor, K., Howardy, A., Rizzi, A.A., and Raibert, M. (2010, January 4\u20138). Autonomous navigation for BigDog. Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage, Alaska.","DOI":"10.1109\/ROBOT.2010.5509226"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1109\/JIOT.2018.2812300","article-title":"A survey of the state-of-the-art localization techniques and their potentials for autonomous vehicle applications","volume":"5","author":"Kuutti","year":"2018","journal-title":"IEEE Int. Things J."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Yurtsever, E., Lambert, J., Carballo, A., and Takeda, K. (2019). A survey of autonomous driving: Common practices and emerging technologies. arXiv.","DOI":"10.1109\/ACCESS.2020.2983149"},{"key":"ref_31","unstructured":"Adams, M., Adams, M.D., and Jose, E. (2012). Robotic Navigation and Mapping With Radar, Artech House."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1002\/rob.21605","article-title":"Localizing ground penetrating radar: A step toward robust autonomous ground vehicle localization","volume":"33","author":"Cornick","year":"2016","journal-title":"J. Field Robot."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1109\/JOE.2013.2278891","article-title":"AUV navigation and localization: A review","volume":"39","author":"Paull","year":"2013","journal-title":"IEEE J. Ocean. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Panish, R., and Taylor, M. (2011). Achieving high navigation accuracy using inertial navigation systems in autonomous underwater vehicles. OCEANS 2011 IEEE-Spain, IEEE.","DOI":"10.1109\/Oceans-Spain.2011.6003517"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1109\/SURV.2012.121912.00075","article-title":"A survey of indoor inertial positioning systems for pedestrians","volume":"15","author":"Harle","year":"2013","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1109\/TBME.2010.2060723","article-title":"Zero-velocity detection\u2014An algorithm evaluation","volume":"57","author":"Skog","year":"2010","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_37","first-page":"1","article-title":"Zero-velocity detection\u2014A Bayesian approach to adaptive thresholding","volume":"3","author":"Skog","year":"2019","journal-title":"IEEE Sens. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Cort\u00e9s, S., Solin, A., and Kannala, J. (2018, January 17\u201320). Deep learning based speed estimation for constraining strapdown inertial navigation on smartphones. Proceedings of the 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), Aalborg, Denmark.","DOI":"10.1109\/MLSP.2018.8516710"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wagstaff, B., and Kelly, J. (2018, January 24\u201327). LSTM-based zero-velocity detection for robust inertial navigation. Proceedings of the 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Nantes, France.","DOI":"10.1109\/IPIN.2018.8533770"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Kone, Y., Zhu, N., Renaudin, V., and Ortiz, M. (2020). Machine Learning-Based Zero-Velocity Detection for Inertial Pedestrian Navigation. IEEE Sens. J.","DOI":"10.1109\/JSEN.2020.2999863"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Shu, Y., Shin, K.G., He, T., and Chen, J. (2015, January 7\u201311). Last-mile navigation using smartphones. Proceedings of the 21st Annual International Conference on Mobile Computing And Networking, Paris, France.","DOI":"10.1145\/2789168.2790099"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/JBHI.2017.2679486","article-title":"Mobile stride length estimation with deep convolutional neural networks","volume":"22","author":"Hannink","year":"2017","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cja.2014.12.001","article-title":"Navigation sensors and systems in GNSS degraded and denied environments","volume":"28","author":"Schmidt","year":"2015","journal-title":"Chin. J. Aeron."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1606","DOI":"10.1109\/TIM.2006.881033","article-title":"The utilization of artificial neural networks for multisensor system integration in navigation and positioning instruments","volume":"55","author":"Chiang","year":"2006","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1088\/0957-0233\/17\/10\/033","article-title":"Bridging GPS outages using neural network estimates of INS position and velocity errors","volume":"17","author":"Semeniuk","year":"2006","journal-title":"Meas. Sci. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"4653","DOI":"10.1016\/j.eswa.2013.02.002","article-title":"A low-cost INS\/GPS integration methodology based on random forest regression","volume":"40","author":"Adusumilli","year":"2013","journal-title":"Expert Syst. Appl."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.neucom.2015.03.080","article-title":"A novel hybrid approach utilizing principal component regression and random forest regression to bridge the period of GPS outages","volume":"166","author":"Adusumilli","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_48","first-page":"300","article-title":"A note on the use of principal components in regression","volume":"31","author":"Jolliffe","year":"1982","journal-title":"J. R. Stat. Soc. Ser. C Appl. Stat."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"61296","DOI":"10.1109\/ACCESS.2019.2911025","article-title":"A Fusion Methodology to Bridge GPS Outages for INS\/GPS Integrated Navigation System","volume":"7","author":"Zhang","year":"2019","journal-title":"IEEE Access"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1941","DOI":"10.1109\/TITS.2019.2909064","article-title":"AbolDeepIO: A novel deep inertial odometry network for autonomous vehicles","volume":"21","author":"Esfahani","year":"2019","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Chen, C., Lu, X., Markham, A., and Trigoni, N. (2018, January 2\u20137). Ionet: Learning to cure the curse of drift in inertial odometry. Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, LA, USA.","DOI":"10.1609\/aaai.v32i1.12102"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Brossard, M., Barrau, A., and Bonnabel, S. (2019). RINS-W: Robust inertial navigation system on wheels. arXiv.","DOI":"10.1109\/IROS40897.2019.8968593"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Brossard, M., Barrau, A., and Bonnabel, S. (2019). AI-IMU dead-reckoning. arXiv.","DOI":"10.1109\/TIV.2020.2980758"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Silva do Monte Lima, J.P., Uchiyama, H., and Taniguchi, R.i. (2019). End-to-End Learning Framework for IMU-Based 6-DOF Odometry. Sensors, 19.","DOI":"10.3390\/s19173777"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Zhang, H., Li, T., Yin, L., Liu, D., Zhou, Y., Zhang, J., and Pan, F. (2019). A Novel KGP Algorithm for Improving INS\/GPS Integrated Navigation Positioning Accuracy. Sensors, 19.","DOI":"10.3390\/s19071623"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2016.08.001","article-title":"Improving positioning accuracy of vehicular navigation system during GPS outages utilizing ensemble learning algorithm","volume":"35","author":"Li","year":"2017","journal-title":"Inform. Fus."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Yan, H., Herath, S., and Furukawa, Y. (2019). RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods. arXiv.","DOI":"10.1109\/ICRA40945.2020.9196860"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"5653","DOI":"10.1109\/LRA.2020.3007421","article-title":"TLIO: Tight Learned Inertial Odometry","volume":"5","author":"Liu","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_59","first-page":"44","article-title":"The PNT boom: Future trends in integrated navigation","volume":"8","author":"Groves","year":"2013","journal-title":"Inside GNSs"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Groves, P.D., Wang, L., Walter, D., Martin, H., Voutsis, K., and Jiang, Z. (2014, January 5\u20138). The four key challenges of advanced multisensor navigation and positioning. Proceedings of the 2014 IEEE\/ION, Position, Location and Navigation Symposium-PLANS 2014, Monterey, CA, USA.","DOI":"10.1109\/PLANS.2014.6851443"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Cole, J., Mohammadzadeh, F., Bollinger, C., Latif, T., Bozkurt, A., and Lobaton, E. A study on motion mode identification for cyborg roaches. Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA.","DOI":"10.1109\/ICASSP.2017.7952637"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Madgwick, S.O., Harrison, A.J., and Vaidyanathan, R. (July, January 29). Estimation of IMU and MARG orientation using a gradient descent algorithm. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Z\u00fcrich, Switzerland.","DOI":"10.1109\/ICORR.2011.5975346"},{"key":"ref_63","unstructured":"Kirk, D.E. (2004). Optimal Control Theory: An Introduction, Courier Corporation."},{"key":"ref_64","unstructured":"Kincaid, D., Kincaid, D.R., and Cheney, E.W. (2009). Numerical Analysis: Mathematics of Scientific Computing, American Mathematical Society."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"497","DOI":"10.2307\/2372560","article-title":"On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents","volume":"79","author":"Dubins","year":"1957","journal-title":"Amer. J. Math."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"367","DOI":"10.2140\/pjm.1990.145.367","article-title":"Optimal paths for a car that goes both forwards and backwards","volume":"145","author":"Reeds","year":"1990","journal-title":"Pac. J. Math."},{"key":"ref_67","unstructured":"MATLAB (2018). Statistics and Machine Learning Toolbox Version 11.3: MATLAB Release 2018a, The MathWorks Inc."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Kuipers, J.B. (1999). Quaternions and Rotation Sequences, Princeton University Press.","DOI":"10.1515\/9780691211701"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Cole, J., Agcayazi, T., Latif, T., Bozkurt, A., and Lobaton, E. (November, January 29). Speed estimation based on gait analysis for biobotic agents. Proceedings of the 2017 IEEE SENSORS, Glasgow, UK.","DOI":"10.1109\/ICSENS.2017.8234224"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1002\/widm.8","article-title":"Classification and regression trees","volume":"1","author":"Loh","year":"2011","journal-title":"Wiley Int. Revi. Data Min. Knowl. Discov."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1111\/insr.12016","article-title":"Fifty years of classification and regression trees","volume":"82","author":"Loh","year":"2014","journal-title":"Int. Stat. Rev."},{"key":"ref_73","unstructured":"Breiman, L., Friedman, J., Stone, C.J., and Olshen, R.A. (1984). Classification and rEgression Trees, CRC Press."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Zhang, C., and Ma, Y. (2012). Ensemble Machine Learning: Methods and Applications, Springer.","DOI":"10.1007\/978-1-4419-9326-7"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2009). The eLements of Statistical Learning: Data Mining, Inference, and Prediction, Springer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref_76","unstructured":"MATLAB (2018). Optimization Toolbox Version 8.1: MATLAB Release 2018a, The MathWorks Inc."},{"key":"ref_77","unstructured":"Nocedal, J., and Wright, S. (2006). Numerical Optimization, Springer."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Xiong, H., Agcayazi, T., Latif, T., Bozkurt, A., and Sichitiu, M.L. (November, January 29). Towards acoustic localization for biobotic sensor networks. Proceedings of the 2017 IEEE SENSORS, Glasgow, UK.","DOI":"10.1109\/ICSENS.2017.8234245"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge detection","volume":"PAMI-8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/16\/4486\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T01:58:42Z","timestamp":1719885522000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/16\/4486"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,11]]},"references-count":79,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["s20164486"],"URL":"https:\/\/doi.org\/10.3390\/s20164486","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2020,8,11]]}}}