Stable Pushing

Stable pushing, a crucial aspect of non-prehensile manipulation, focuses on reliably moving objects using a pushing action, often with a robotic agent. Current research emphasizes robust planning algorithms, including model predictive control and Monte Carlo Tree Search, often incorporating contact modeling and uncertainty handling through techniques like quasi-static belief dynamics and non-parametric learning. These advancements aim to improve the efficiency and reliability of pushing actions in cluttered environments, with applications ranging from warehouse automation to assembly tasks. The ultimate goal is to develop more versatile and adaptable robotic systems capable of handling a wider range of objects and scenarios.