{"ID":2869818,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.13903","arxiv_id":"2509.13903","title":"PhysicalAgent: Towards General Cognitive Robotics with Foundation World Models","abstract":"We introduce PhysicalAgent, an agentic framework for robotic manipulation that integrates iterative reasoning, diffusion-based video generation, and closed-loop execution. Given a textual instruction, our method generates short video demonstrations of candidate trajectories, executes them on the robot, and iteratively re-plans in response to failures. This approach enables robust recovery from execution errors. We evaluate PhysicalAgent across multiple perceptual modalities (egocentric, third-person, and simulated) and robotic embodiments (bimanual UR3, Unitree G1 humanoid, simulated GR1), comparing against state-of-the-art task-specific baselines. Experiments demonstrate that our method consistently outperforms prior approaches, achieving up to 83% success on human-familiar tasks. Physical trials reveal that first-attempt success is limited (20-30%), yet iterative correction increases overall success to 80% across platforms. These results highlight the potential of video-based generative reasoning for general-purpose robotic manipulation and underscore the importance of iterative execution for recovering from initial failures. Our framework paves the way for scalable, adaptable, and robust robot control.","short_abstract":"We introduce PhysicalAgent, an agentic framework for robotic manipulation that integrates iterative reasoning, diffusion-based video generation, and closed-loop execution. Given a textual instruction, our method generates short video demonstrations of candidate trajectories, executes them on the robot, and iteratively...","url_abs":"https://arxiv.org/abs/2509.13903","url_pdf":"https://arxiv.org/pdf/2509.13903v1","authors":"[\"Artem Lykov\",\"Jeffrin Sam\",\"Hung Khang Nguyen\",\"Vladislav Kozlovskiy\",\"Yara Mahmoud\",\"Valerii Serpiva\",\"Miguel Altamirano Cabrera\",\"Mikhail Konenkov\",\"Dzmitry Tsetserukou\"]","published":"2025-09-17T11:09:03Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[\"Diffusion Model\"]","has_code":false}