Most humanoid loco-manipulation controllers require human motion data to learn whole-body coordination and posture, leaving policies reliant on external sources to provide this data. We present OCLO (Online-posture Compliant LOco-manipulation), a humanoid loco-manipulation system trained without human motion data and c...
Seung-Bock Yeom, Zhen-Yu Wu, Jaeyoung Huh et al.· 0 citations
Learning from Hindsight is presented, which brings hindsight relabeling to RL post-training of VLAs by scoring failed rollouts against the tasks they actually achieved, and achieves 5 times improvement in sample efficiency, and outperforms a dense progress-reward baseline on out-of-distribution LIBERO-PRO tasks.
Iris Xu, Sunshine Jiang, John Marangola et al.· arXiv.org· 0 citations
Mobile manipulators on construction sites offer considerable potential for increasing productivity, as the transport of materials and the execution of precise assembly work can be increasingly automated. However, the coordination of several such robots is a complex planning task, as task assignment, navigation, and rea...
Charlotte Stein, Yuheng Zhi, Michael C. Yip et al.· 2026 IEEE/ASME International...· 0 citations
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