{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T02:41:22Z","timestamp":1769740882245,"version":"3.49.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8]]},"abstract":"<jats:p>Legged locomotion in a complex environment requires careful planning of the footholds of legged robots. In this paper, a novel Deep Reinforcement Learning (DRL) method is proposed to implement multi-contact motion planning for hexapod robots moving on uneven plum-blossom piles. First, the motion of hexapod robots is formulated as a Markov Decision Process (MDP) with a speci\ufb01ed reward function. Second, a transition feasibility model is proposed for hexapod robots, which describes the feasibility of the state transition under the condition of satisfying kinematics and dynamics, and in turn determines the rewards. Third, the footholds and Center-of-Mass (CoM) sequences are sampled from a diagonal Gaussian distribution and the sequences are optimized through learning the optimal policies using the designed DRL algorithm. Both of the simulation and experimental results on physical systems demonstrate the feasibility and efficiency of the proposed method. Videos are shown at https:\/\/videoviewpage.wixsite.com\/mcrl.<\/jats:p>","DOI":"10.24963\/ijcai.2021\/328","type":"proceedings-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:00:49Z","timestamp":1628679649000},"page":"2381-2388","source":"Crossref","is-referenced-by-count":11,"title":["Deep Reinforcement Learning for Multi-contact Motion Planning of Hexapod Robots"],"prefix":"10.24963","author":[{"given":"Huiqiao","family":"Fu","sequence":"first","affiliation":[{"name":"School of Management and Engineering, Nanjing University"},{"name":"Advanced Institute of Information Technology (AIIT), Peking University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaiqiang","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Management and Engineering, Nanjing University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"Advanced Institute of Information Technology (AIIT), Peking University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenqi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Advanced Institute of Information Technology (AIIT), Peking University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinpeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Southwest University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guizhou","family":"Deng","sequence":"additional","affiliation":[{"name":"Southwest University of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[{"name":"Advanced Institute of Information Technology (AIIT), Peking University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunlin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Management and Engineering, Nanjing University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}","theme":"Artificial Intelligence","location":"Montreal, Canada","acronym":"IJCAI-2021","number":"30","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2021,8,19]]},"end":{"date-parts":[[2021,8,27]]}},"container-title":["Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T11:02:39Z","timestamp":1628679759000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2021\/328"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2021,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2021\/328","relation":{},"subject":[],"published":{"date-parts":[[2021,8]]}}}