Paper ID: 2204.07268

Visual Pressure Estimation and Control for Soft Robotic Grippers

Patrick Grady, Jeremy A. Collins, Samarth Brahmbhatt, Christopher D. Twigg, Chengcheng Tang, James Hays, Charles C. Kemp

Soft robotic grippers facilitate contact-rich manipulation, including robust grasping of varied objects. Yet the beneficial compliance of a soft gripper also results in significant deformation that can make precision manipulation challenging. We present visual pressure estimation & control (VPEC), a method that infers pressure applied by a soft gripper using an RGB image from an external camera. We provide results for visual pressure inference when a pneumatic gripper and a tendon-actuated gripper make contact with a flat surface. We also show that VPEC enables precision manipulation via closed-loop control of inferred pressure images. In our evaluation, a mobile manipulator (Stretch RE1 from Hello Robot) uses visual servoing to make contact at a desired pressure; follow a spatial pressure trajectory; and grasp small low-profile objects, including a microSD card, a penny, and a pill. Overall, our results show that visual estimates of applied pressure can enable a soft gripper to perform precision manipulation.

Submitted: Apr 14, 2022