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MAP-VLA: Memory-Augmented Prompting for Vision-Language-Action Model in Robotic Manipulation
Runhao Li, Wenkai Guo, Zhenyu Wu +5
Pre-trained Vision-Language-Action (VLA) models have achieved remarkable success in improving robustness and generalization for end-to-end robotic manipulation. However, these mode…
MoTo: A Zero-shot Plug-in Interaction-aware Navigation for General Mobile Manipulation
Zhenyu Wu, Angyuan Ma, Xiuwei Xu +5
Mobile manipulation stands as a core challenge in robotics, enabling robots to assist humans across varied tasks and dynamic daily environments. Conventional mobile manipulation ap…
SafeBimanual: Diffusion-based Trajectory Optimization for Safe Bimanual Manipulation
Haoyuan Deng, Wenkai Guo, Qianzhun Wang +2
Bimanual manipulation has been widely applied in household services and manufacturing, which enables the complex task completion with coordination requirements. Recent diffusion-ba…
MoManipVLA: Transferring Vision-language-action Models for General Mobile Manipulation
Zhenyu Wu, Yuheng Zhou, Xiuwei Xu +2
Mobile manipulation is the fundamental challenge for robotics to assist humans with diverse tasks and environments in everyday life. However, conventional mobile manipulation appro…