Robotics paper index
Object-Informed Model Predictive Path Integral Control for Non-Prehensile Robot Manipulation
One-line summary
A robotics research paper on Object-Informed Model Predictive Path Integral Control for Non-Prehensile Robot Manipulation.
Engineering notes
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Chinese explanation / 中文解读
中文解读待补充：本站会优先为 VLA、具身智能、人形机器人控制、机器人操作等高价值论文补充中文说明。
Original abstract
Long-horizon planning for non-prehensile robot manipulation is challenging due to underactuated and discontinuous interactions. We propose a hierarchical formulation of model predictive path integral (MPPI) control that guides robot-level planning with a separately computed object-level plan to achieve efficient long-horizon prediction. We first solve a simplified object-only problem, assuming the object can be actuated directly, and use the planned object trajectory as a reference in solving the joint robot-object planning problem. We evaluate our method in both simulation and hardware using a 6-DoF xArm6 manipulator to perform object pushing tasks in which the target object must reach a goal while avoiding static obstacles, necessitating non-myopic reasoning. Our object-informed MPPI increases task success by 40\% with a 26\% faster control frequency in simulation, and by 20\% in real experiments with similar computation as regular MPPI.
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