Real-time control improves whole-hand grasping under disturbances
Real-Time Force Regulation for Whole-Hand Dexterous Grasping
Robotics
Summary
Holding objects firmly with a robotic hand is tricky because the object and the hand's contact points can move or shift. The authors present a method that constantly adjusts how the robotic hand applies force across all fingers in real time without needing touch sensors. This method helps the robot keep a stable grip even when the object moves or is pushed. They tested it in simulations and with a real robotic hand and showed it recovers better from disturbances than older methods.
What this means in practice
- •For robotic system integrators: Enable robotic hands to maintain and recover stable grasps on moving objects without tactile sensors, improving handling reliability.
- •For industrial automation teams: Improve robotic manipulation in assembly or packaging lines where objects shift or are disturbed during grasping.
Authors
Sang Min Kim, Alexander Alexiev, Tzu-Yuan Lin, Sangbae Kim, Young Min Kim, Yonghyeon Lee
Abstract
Robust dexterous grasping requires maintaining physical stability despite contacts interactively evolving across the entire hand. A precomputed force distribution can easily fail under object motion, modeling errors, or external disturbances. In this paper, we present a framework for real-time force regulation over dynamically changing whole-hand contacts. Our method geometrically estimates contacts across all hand links using a tracked object model and proprioception, without requiring tactile sensing at those contacts. It repeatedly recomputes the desired contact-force distribution subject to friction constraints, actuator limits, and an actuation-consistency constraint motivated by classical whole-limb force analysis. We integrate this force-regulation controller with reactive reaching, enabling the hand to acquire a grasp, maintain it under disturbances, and regrasp after losing the object. Simulation experiments without gravity demonstrate improved grasp retention over fixed-allocation and fingertip-only execution under controlled perturbations, while real-world experiments on a 27-DoF arm-hand system demonstrate grasp maintenance and recovery under human-applied disturbances as contacts evolve across the whole hand. Project page: https://sangminkim-99.github.io/reactive-grasp-whole-hand/