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DAM-VLA: A Dynamic Action Model-Based Vision-Language-Action Framework for Robot Manipulation
- Peng, Xiongfeng;
- Yu, Jiaqian;
- Li, Dingzhe;
- Jin, Yixiang;
- Xu, Lu;
- ... Jang, Sujin;
- 외 5명
초록
In dynamic environments such as warehouses, hospitals, and homes, robots must seamlessly transition between gross motion and precise manipulations to complete complex tasks. However, current Vision-Language-Action (VLA) frameworks, largely adapted from pre-trained Vision-Language Models (VLMs), often struggle to reconcile general task adaptability with the specialized precision required for intricate manipulation. To address this challenge, we propose DAM-VLA, a dynamic action model-based VLA framework. DAM-VLA integrates VLM reasoning with diffusion-based action models specialized for arm and gripper control. Specifically, it introduces (i) an action routing mechanism, using task-specific visual and linguistic cues to select appropriate action models (e.g., arm movement or gripper manipulation), (ii) a dynamic action model that fuses high-level VLM cognition with low-level visual features to predict actions, and (iii) a dual-scale action weighting mechanism that enables dynamic coordination between the arm-movement and gripper-manipulation models. Across extensive evaluations, DAM-VLA achieves superior success rates compared to state-of-the-art VLA methods in simulated (SIMPLER, FurnitureBench) and real-world settings, showing robust generalization from standard pick-and-place to demanding long-horizon and contact-rich tasks.
- 제목
- DAM-VLA: A Dynamic Action Model-Based Vision-Language-Action Framework for Robot Manipulation
- 저자
- Peng, Xiongfeng; Yu, Jiaqian; Li, Dingzhe; Jin, Yixiang; Xu, Lu; Mao, Yamin; Zhang, Chao; Li, Weiming; Jang, Sujin; Lee, Dongwook; Ji, Daehyun
- 발행일
- 2026-03
- 유형
- Proceeding
- 저널명
- IEEE International Conference on Robotics and Automation
- 페이지
- 1 ~ 8
- 언어
- ENG
- 출판사
- IEEE Robotics and Automation Society
- 분량
- 8 페이지