{"id":4256,"date":"2022-06-30T15:34:57","date_gmt":"2022-06-30T07:34:57","guid":{"rendered":"https:\/\/inventec2.mjitec.tw\/?page_id=4256"},"modified":"2024-01-17T11:11:54","modified_gmt":"2024-01-17T03:11:54","slug":"transition-motion-tensor","status":"publish","type":"page","link":"https:\/\/inventec2.mjitec.tw\/en\/ai\/transition-motion-tensor\/","title":{"rendered":"Transition Motion Tensor"},"content":{"rendered":"

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Transition Motion Tensor: A Data-Driven Approach for Versatile and Controllable Agents in Physically Simulated Environments <\/h2>\n\t <\/div><\/div>[vc_column_text css=”.vc_custom_1660542162721{margin-bottom: 20px !important;}”]<\/p>\n
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SIGGRAPH Asia 2021 Technical Communications<\/p>\n<\/div>\n

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Authors<\/h6>\n<\/div>\n

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Soeseno, Jonathan Hans* and Luo, Ying-Sheng* and Chen, Trista Pei-Chun and Chen, Wei-Chao (*denotes joint first authors)<\/p>\n<\/div>\n

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Published<\/h6>\n<\/div>\n

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2021\/12\/14<\/p>\n<\/div>\n

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Abstract <\/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 Motion Tensor, a data-driven framework that creates novel and physically accurate transitions outside of the motion dataset. It enables simulated characters to adopt new motion skills efficiently and robustly without modifying existing ones. Given several physically simulated controllers specializing in different motions, the tensor serves as a temporal guideline to transition between them.<\/p>\n

Through querying the tensor for transitions that best fit user-defined preferences, we can create a unified controller capable of producing novel transitions and solving complex tasks that may require multiple motions to work coherently. We apply our framework on both quadrupeds and bipeds, perform quantitative and qualitative evaluations on transition quality, and demonstrate its capability of tackling complex motion planning problems while following user control directives.[\/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]JTNDaWZyYW1lJTIwd2lkdGglM0QlMjIxMjQwJTIyJTIwaGVpZ2h0JTNEJTIyODAwJTIyJTIwc3JjJTNEJTIyaHR0cHMlM0ElMkYlMkZ3d3cueW91dHViZS5jb20lMkZlbWJlZCUyRjlOelJTWnlBT2lZJTIyJTIwdGl0bGUlM0QlMjJZb3VUdWJlJTIwdmlkZW8lMjBwbGF5ZXIlMjIlMjBmcmFtZWJvcmRlciUzRCUyMjAlMjIlMjBhbGxvdyUzRCUyMmFjY2VsZXJvbWV0ZXIlM0IlMjBhdXRvcGxheSUzQiUyMGNsaXBib2FyZC13cml0ZSUzQiUyMGVuY3J5cHRlZC1tZWRpYSUzQiUyMGd5cm9zY29wZSUzQiUyMHBpY3R1cmUtaW4tcGljdHVyZSUyMiUyMGFsbG93ZnVsbHNjcmVlbiUzRSUzQyUyRmlmcmFtZSUzRQ==[\/vc_raw_html][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column]

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Keywords<\/h2>\n

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Download<\/h3>\n

[\/vc_column_text][vc_row_inner content_placement=”middle”][vc_column_inner el_class=”download_btn_wrap”][vc_btn title=”PDF” style=”flat” color=”white” align=”center” link=”url:https%3A%2F%2Farxiv.org%2Fpdf%2F2111.15072.pdf|target:_blank” el_class=”download_btn”][vc_btn title=”Source code” style=”flat” color=”white” align=”center” link=”url:https%3A%2F%2Fgithub.com%2Finventec-ai-center%2Ftransition_motion_tensor|target:_blank” el_class=”download_btn”][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

[vc_row full_width=”stretch_row”][vc_column][vc_row_inner el_class=”md-full-col”][vc_column_inner el_class=”m_p” width=”1\/2″][vc_column_text css=”.vc_custom_1660542162721{margin-bottom: 20px !important;}”] SIGGRAPH Asia 2021 Technical Communications [\/vc_column_text][vc_column_text css=”.vc_custom_1660548270977{margin-bottom: 5px !important;}”] Authors [\/vc_column_text][vc_column_text css=”.vc_custom_1660542182354{margin-bottom: 20px !important;}”] Soeseno, Jonathan Hans* and Luo, Ying-Sheng* and Chen, Trista Pei-Chun and Chen, Wei-Chao (*denotes joint first authors) [\/vc_column_text][vc_column_text css=”.vc_custom_1660548281108{margin-bottom: 5px !important;}”] Published [\/vc_column_text][vc_column_text] 2021\/12\/14 [\/vc_column_text][\/vc_column_inner][vc_column_inner el_class=”m_p” width=”1\/2″][vc_single_image image=”2522″ img_size=”full”][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column][\/vc_column][\/vc_row][vc_row full_width=”stretch_row”][vc_column][vc_row_inner content_placement=”top” css=”.vc_custom_1657794580528{margin-bottom: 20px…<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":4975,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4256","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/pages\/4256","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/comments?post=4256"}],"version-history":[{"count":0,"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/pages\/4256\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/pages\/4975"}],"wp:attachment":[{"href":"https:\/\/inventec2.mjitec.tw\/en\/wp-json\/wp\/v2\/media?parent=4256"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}