3 papers
cs.RO2026
Refuse the Harm, Complete the Task via Graph-of-Rules Planning for LLM-Enabled Robots
Ali Taheri, Alireza Taban, Qizhou Wang +1
Large Language Models (LLMs) are increasingly used in embodied AI for robotic manipulation and planning, but their deployment in physical systems exposes vulnerabilities such as ja…
cs.AI2026
Who Improves the Robot? Toward Physical Recursive Self-Improvement
Hai Zhou, Fan Yang, Zeyi Chen +27
Robots are increasingly autonomous in task execution, yet their improvement remains largely human-driven. This study investigates Physical Recursive Self-Improvement (Physical RSI)…
cs.RO2026
RoboFoundry: System-as-Policy Evolution for Self-Learning Embodied Agents
Jingsong Liang, Shuhao Liao, Shizhe Zhang +15
A foundation model should not act in isolation as an embodied agent. Yet, existing methods often optimize individual components of the agent stack, such as memory, context, skills,…