Robust Object Manipulation for Tactile-based Blind Grasping
This addresses a gap in robotic manipulation for scenarios where only tactile and proprioceptive sensors are available, though it appears incremental as it builds on existing tactile grasping work.
The paper tackled the problem of robotic grasping without prior knowledge of object properties by proposing a robust control law for tactile-based blind grasping, achieving semi-global asymptotic and exponential stability in simulations and experiments.
Tactile-based blind grasping addresses realistic robotic grasping in which the hand only has access to proprioceptive and tactile sensors. The robotic hand has no prior knowledge of the object/grasp properties, such as object weight, inertia, and shape. There exists no manipulation controller that rigorously guarantees object manipulation in such a setting. Here, a robust control law is proposed for object manipulation in tactile-based blind grasping. The analysis ensures semi-global asymptotic and exponential stability in the presence of model uncertainties and external disturbances that are neglected in related work. Simulation and experimental results validate the effectiveness of the proposed approach.