Proactive tactile exploration for object-agnostic shape reconstruction from minimal visual priors

TL;DR

This paper introduces a proactive tactile exploration method combined with iterative shape reconstruction to accurately perceive object surfaces with minimal visual priors, enhancing robotic manipulation capabilities.

Contribution

It presents a novel iterative shape reconstruction approach integrated with a proactive tactile exploration strategy to efficiently and accurately model object surfaces.

Findings

Effective shape reconstruction with minimal contacts

Reduced uncertainty in surface estimation

Validated in simulation and real-world experiments

Abstract

The perception of an object's surface is important for robotic applications enabling robust object manipulation. The level of accuracy in such a representation affects the outcome of the action planning, especially during tasks that require physical contact, e.g. grasping. In this paper, we propose a novel iterative method for 3D shape reconstruction consisting of two steps. At first, a mesh is fitted on data points acquired from the object's surface, based on a single primitive template. Subsequently, the mesh is properly adjusted to adequately represent local deformities. Moreover, a novel proactive tactile exploration strategy aims at minimizing the total uncertainty with the least number of contacts, while reducing the risk of contact failure in case the estimated surface differs significantly from the real one. The performance of the methodology is evaluated both in 3D simulation and on a real setup.