Manipulation and Grasping

The Manipulation and Grasping research area develops algorithms, testbeds, and end-effectors for advancing robotic manipulation and grasping by leveraging human-inspired strategies for physical interaction and machine learning techniques. This research uses a variety of human-robot interaction paradigms to collect data, including physical interactions, and fuse insights from computer simulation and physical experiments. Novel testbeds are developed for evaluating complex manipulation and grasping tasks (e.g., underwater grasping and apple picking).

The manipulation and grasping application areas span from underwater grasping to in-hand manipulation to apple picking. Real-world domains include marine robotics, agriculture, and manufacturing.