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Guided Decoding for Robot Motion Generation and Adaption
March 25, 2024, 4:42 a.m. | Nutan Chen, Elie Aljalbout, Botond Cseke, Patrick van der Smagt
cs.LG updates on arXiv.org arxiv.org
Abstract: We address motion generation for high-DoF robot arms in complex settings with obstacles, via points, etc. A significant advancement in this domain is achieved by integrating Learning from Demonstration (LfD) into the motion generation process. This integration facilitates rapid adaptation to new tasks and optimizes the utilization of accumulated expertise by allowing robots to learn and generalize from demonstrated trajectories.
We train a transformer architecture on a large dataset of simulated trajectories. This architecture, based …
abstract advancement arxiv cs.lg cs.ro decoding domain etc integration obstacles process robot tasks type via
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