Manipulation Domain

Robotic manipulation research focuses on enabling robots to dexterously interact with and manipulate objects in complex environments. Current efforts concentrate on developing robust and generalizable manipulation strategies using reinforcement learning, visual feedback (including diffusion models for zero-shot learning), and sophisticated contact modeling to handle diverse object shapes and interactions, including multiple and intermittent contacts. These advancements are crucial for improving the autonomy and adaptability of robots in various applications, ranging from industrial automation to assistive robotics and human-robot collaboration.