Fast Model-Based Contact Patch and Pose Estimation for Highly Deformable Dense-Geometry Tactile Sensors

Abstract

Modeling deformable contact is a well-known problem in soft robotics and is particularly challenging for compliant interfaces that permit large deformations. We present a model for the behavior of a highly deformable dense geometry sensor in its interaction with objects; the forward model predicts the elastic deformation of a mesh given the pose and geometry of a contacting rigid object. We use this model to develop a fast approximation to solve the inverse problem: estimating the contact patch when the sensor is deformed by arbitrary objects. This inverse model can be easily identified through experiments and is formulated as a sparse Quadratic Program (QP) that can be solved efficiently online. The proposed model serves as the first stage of a pose estimation pipeline for robot manipulation. We demonstrate the proposed inverse model through real-time estimation of contact patches on a contact-rich manipulation problem in which oversized fingers screw a nut onto a bolt, and as part of a complete pipeline for pose-estimation and tracking based on the Iterative Closest Point (ICP) algorithm. Our results demonstrate a path towards realizing soft robots with highly compliant surfaces that perform complex real-world manipulation tasks.