Movable Obstacle

Movable obstacle research focuses on enabling robots and autonomous systems to navigate and interact with dynamic environments containing objects that can be moved. Current research emphasizes real-time perception (e.g., using LiDAR) for obstacle detection and classification, coupled with advanced planning algorithms like RRT*, CBFs, and MPC to generate safe and efficient paths, often incorporating obstacle manipulation strategies. This field is crucial for advancing robotics in cluttered, unpredictable settings, with applications ranging from warehouse automation and search-and-rescue to autonomous driving and assistive technologies.