{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T08:34:13Z","timestamp":1761294853098,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T00:00:00Z","timestamp":1751587200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Research Program of Jiangsu","award":["BK20240313"],"award-info":[{"award-number":["BK20240313"]}]},{"name":"Wuxi Young Scientific and Technological Talent Support","award":["BK20240313"],"award-info":[{"award-number":["BK20240313"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Hexapod robots that use external sensors to sense the environment are susceptible to factors such as light intensity or foggy weather. This effect leads to a drastic decrease in the motility of the hexapod robot. This paper proposes a motion control strategy for a blind hexapod robot. The hexapod robot is symmetrical and its environmental sensing capability is obtained by collecting proprioceptive signals from internal sensors, allowing it to pass through rugged terrain without the need for external sensors. The motion gait of the hexapod robot is generated by a central pattern generator (CPG) network constructed by Hopf oscillators. This gait is a periodic gait controlled by specific parameters given in advance. A policy network is trained in the target terrain using deep reinforcement learning (DRL). The trained policy network is able to fine-tune specific parameters by acquiring information about the current terrain. Thus, an adaptive gait is obtained. The experimental results show that the adaptive gait enables the hexapod robot to stably traverse various complex terrains.<\/jats:p>","DOI":"10.3390\/sym17071058","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T05:54:52Z","timestamp":1751608492000},"page":"1058","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Motion Control Strategy for a Blind Hexapod Robot Based on Reinforcement Learning and Central Pattern Generator"],"prefix":"10.3390","volume":"17","author":[{"given":"Lei","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automation, Wuxi University, Wuxi 214105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiwen","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoxiao","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weidong","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Wuxi University, Wuxi 214105, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9960-9040","authenticated-orcid":false,"given":"Yiyang","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215137, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"eaau0307","DOI":"10.1126\/scirobotics.aau0307","article-title":"AntBot: A six-legged walking robot able to home like desert ants in outdoor environments","volume":"4","author":"Dupeyroux","year":"2019","journal-title":"Sci. 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