Scenario Convex Programs for Dexterous Manipulation under Modeling Uncertainties

TL;DR

This paper introduces a scenario convex programming framework for designing robust controllers for dexterous manipulation under uncertainties, enabling reliable manipulation across various contact points and operating conditions.

Contribution

It presents a novel approach combining scenario convex programming with robust pole placement to handle uncertainties in multi-fingered robotic manipulation.

Findings

Successful simulation of manipulation with contact location errors

Robust control performance across multiple initial grasps

Quantified probabilistic feasibility of the control strategy

Abstract

This paper proposes a new framework to design a controller for the dexterous manipulation of an object by a multi-fingered hand. To achieve a robust manipulation and wide range of operations, the uncertainties on the location of the contact point and multiple operating points are taken into account in the control design by sampling the state space. The proposed control strategy is based on a robust pole placement using LMIs. Moreover, to handle uncertainties and different operating points, we recast our problem as a robust convex program (RCP). We then consider the original RCP as a scenario convex program (SCP) and solve the SCP by sampling the uncertain grasp map parameter and operating points in the state space. For a required probabilistic level of confidence, we quantify the feasibility of the SCP solution based on the number of sampling points. The control strategy is tested in simulation in a case study with contact location error and different initial grasps.