Whole Arm Manipulation

Whole-arm manipulation research focuses on enabling robots to perform complex tasks using their entire arm, not just their end-effectors, mimicking human dexterity. Current efforts concentrate on developing robust control algorithms, including neural networks and Koopman operator-based methods, to handle the high dimensionality and nonlinear dynamics of whole-arm movements, often incorporating soft robotics for improved compliance and safety. These advancements are driven by the need for more adaptable and efficient robots capable of handling diverse and challenging real-world scenarios, impacting fields like manufacturing, logistics, and assistive robotics. The development of comprehensive software platforms and low-cost exoskeletons for data collection is also accelerating progress in this area.