{"id":4776,"date":"2023-07-14T14:19:38","date_gmt":"2023-07-14T06:19:38","guid":{"rendered":"https:\/\/inventec2.mjitec.tw\/?page_id=4776"},"modified":"2024-04-23T09:23:27","modified_gmt":"2024-04-23T01:23:27","slug":"expanding-versatility-of-agile-locomotion-through-policy-transitions-using-latent-state-representation","status":"publish","type":"page","link":"https:\/\/inventec2.mjitec.tw\/zh-hans\/ai\/expanding-versatility-of-agile-locomotion-through-policy-transitions-using-latent-state-representation\/","title":{"rendered":"Expanding Versatility of Agile Locomotion"},"content":{"rendered":"

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Expanding Versatility of Agile Locomotion through Policy Transitions Using Latent State Representation <\/h2>\n\t <\/div><\/div>[vc_column_text css=”.vc_custom_1689315005012{margin-bottom: 20px !important;}”]<\/p>\n
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International Conference on Robotics and Automation 2023 (ICRA 2023)<\/p>\n<\/div>\n

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Guilherme Christmann*, Ying-Sheng Luo*, Jonathan Hans Soeseno*, Wei-Chao Chen<\/p>\n<\/div>\n

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May-29<\/p>\n<\/div>\n

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\u6982\u8981 <\/h2>\n\t <\/div><\/div>[\/vc_column_inner][vc_column_inner el_class=”m_p” width=”2\/3″][vc_column_text]This paper proposes the transition-net, a robust transition strategy that expands the versatility of robot locomotion in the real-world setting. To this end, we start with distributing the complexity of different gaits into dedicated locomotion policies applicable to real-world robots. Next, we expand the versatility of the robot by unifying the policies with robust transitions into a single coherent meta-controller by examining the latent state representations. Our approach enables the robot to iteratively expand its skill repertoire and robustly transition between any policy pair in a library. In our framework, adding new skills does not introduce any process that alters the previously learned skills. Moreover, training of a locomotion policy takes less than an hour with a single consumer GPU. Our approach is effective in the real-world and achieves a 19% higher average success rate for the most challenging transition pairs in our experiments compared to existing approaches.[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner content_placement=”middle” el_class=”md-full-col video_wrap”][vc_column_inner el_class=”m_p”][vc_raw_html]JTNDaWZyYW1lJTIwd2lkdGglM0QlMjIxMjQwJTIyJTIwaGVpZ2h0JTNEJTIyODAwJTIyJTIwc3JjJTNEJTIyaHR0cHMlM0ElMkYlMkZ3d3cueW91dHViZS5jb20lMkZlbWJlZCUyRmJFU3pYMjBBa3BnJTIyJTIwdGl0bGUlM0QlMjJZb3VUdWJlJTIwdmlkZW8lMjBwbGF5ZXIlMjIlMjBmcmFtZWJvcmRlciUzRCUyMjAlMjIlMjBhbGxvdyUzRCUyMmFjY2VsZXJvbWV0ZXIlM0IlMjBhdXRvcGxheSUzQiUyMGNsaXBib2FyZC13cml0ZSUzQiUyMGVuY3J5cHRlZC1tZWRpYSUzQiUyMGd5cm9zY29wZSUzQiUyMHBpY3R1cmUtaW4tcGljdHVyZSUyMiUyMGFsbG93ZnVsbHNjcmVlbiUzRSUzQyUyRmlmcmFtZSUzRQ==[\/vc_raw_html][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column]
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