{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T12:29:05Z","timestamp":1724070545841},"reference-count":38,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF\u20102019R1G1A1090040"],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Field Robotics"],"published-print":{"date-parts":[[2021,3]]},"abstract":"Abstract<\/jats:title>This study proposes an autonomous platooning algorithm, composed of velocity, and path planning systems, of multiple ground vehicles in rough terrain. The velocity planning system aims to maintain desired distance between preceding and rear vehicles, and the path planning system generates reliable path to make the vehicles move safely under the given rough environment. To supply a reliable velocity command for the maintenance of the predefined distance, a disturbance observer (DOB)\u2010based control method is employed. An uncertainty\u2010free longitudinal kinematic model is first\u00a0utilized for a nominal velocity generator and the DOB is added to the nominal velocity planner for handling various uncertainties generated during the autonomous platooning. On the other hand, the path planning method is developed by employing a passivity\u2010based model predictive control\u00a0method. With a derived passivity constraint, the stability of the platooning architecture, that is, the platooning performance, is improved. In addition, the proposed path planning method utilizes dynamic and kinematic models of the ground vehicle as equality constraints, and limited range of states and control input as inequality constraints, and perception result about the vehicle's own neighborhood is employed for generation of the path only in traversable region. Its solution is obtained using the particle swarm optimization\u00a0method. Then, to follow the generated velocity and path commands, a well developed driving controller, commercially obtainable, is utilized. Finally, field tests are conducted to validate the performance of the proposed algorithm.<\/jats:p>","DOI":"10.1002\/rob.21984","type":"journal-article","created":{"date-parts":[[2020,9,2]],"date-time":"2020-09-02T04:48:39Z","timestamp":1599022119000},"page":"229-241","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Autonomous platooning of multiple ground vehicles in rough terrain"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-9817-3556","authenticated-orcid":false,"given":"Jongho","family":"Shin","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering Chungbuk\u00a0National University Chungbuk Republic of Korea"}]},{"given":"Dong Jun","family":"Kwak","sequence":"additional","affiliation":[{"name":"Agency for Defense Development Daejeon Republic of Korea"}]},{"given":"Jun","family":"Kim","sequence":"additional","affiliation":[{"name":"Agency for Defense Development Daejeon Republic of Korea"}]}],"member":"311","published-online":{"date-parts":[[2020,9]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917038"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2009.2017962"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.2973799"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2009.2038398"},{"key":"e_1_2_8_6_1","volume-title":"International Technical Conference on Enhanced Safety of Vehicles","author":"Cara I.","year":"2017"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2020.2966176"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/WFCS.2018.8402372"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2921816"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.4271\/2016-01-1875"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/rnc.4394"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/RCAR47638.2019.9044023"},{"key":"e_1_2_8_13_1","unstructured":"Hyundai Rotem. 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