10 papers · 1 filter
Enabling Extensible Embodied Capabilities with Tools
Xueyang Zhou, Zijia Wang, Qianjiang Li +7
Most existing embodied intelligence methods formulate perception, reasoning, planning, and control within a unified parameterized policy. Yet these capabilities are inherently hier…
Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems
Jiabao Ji, Yongchao Chen, Yang Zhang +4
Multi-robot control in cluttered environments is a challenging problem that involves complex physical constraints, including robot-robot collisions, robot-obstacle collisions, and…
EmbodiedClaw: Conversational Workflow Execution for Embodied AI Development
Xueyang Zhou, Yihan Sun, Xijie Gong +4
Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model settings. This shift substantiall…
One-Step Flow Policy: Self-Distillation for Fast Visuomotor Policies
Shaolong Li, Lichao Sun, Yongchao Chen
Generative flow and diffusion models provide the continuous, multimodal action distributions needed for high-precision robotic policies. However, their reliance on iterative sampli…
Simulation to Rules: A Dual-VLM Framework for Formal Visual Planning
Yilun Hao, Yongchao Chen, Chuchu Fan +1
Vision Language Models (VLMs) show strong potential for visual planning but struggle with precise spatial and long-horizon reasoning, while Planning Domain Definition Language (PDD…
Collision- and Reachability-Aware Multi-Robot Control with Grounded LLM Planners
Jiabao Ji, Yongchao Chen, Yang Zhang +4
Large language models (LLMs) have demonstrated strong performance in various robot control tasks. However, their deployment in real-world applications remains constrained. Even sta…