7 papers
RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?
Zhenxuan Fan, Bo Zhang, Yutong Lin +9
Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task compl…
EmbodiedSkills: A Unified Framework for Orchestrating, Training, and Deploying VLA Agents
Wei Wang, Wenqiao Zhang, Yutong Lin +14
Vision-language-action (VLA) models map visual observations and language instructions directly to robot actions, but long-horizon tasks require more than action prediction. An agen…
Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation
Hongyan Feng, Sunlai Chen, Xuanyu Liu +9
Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing methods often force VLMs into…
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7
Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…
VisualThink-VLA: Visual Intermediate Reasoning for Effective and Low-Latency Vision-Language-Action Policies
Mingjian Gao, Wenqiao Zhang, Yuqian Yuan +9
Recent work has begun to equip vision-language-action (VLA) policies with explicit intermediate reasoning. In embodied control, however, textual chain-of-thought is a poor fit: irr…
STRIDE: Automating Reward Design, Deep Reinforcement Learning Training and Feedback Optimization in Humanoid Robotics Locomotion
Zhenwei Wu, Jinxiong Lu, Yuxiao Chen +3
Humanoid robotics presents significant challenges in artificial intelligence, requiring precise coordination and control of high-degree-of-freedom systems. Designing effective rewa…