Dexterous Manipulation of Unknown Objects Using Virtual Contact Points

Andrés Montaño,Raúl Suárez

doi:10.3390/robotics8040086

Abstract

The manipulation of unknown objects is a problem of special interest in robotics since it is not always possible to have exact models of the objects with which the robot interacts. This paper presents a simple strategy to manipulate unknown objects using a robotic hand equipped with tactile sensors. The hand configurations that allow the rotation of an unknown object are computed using only tactile and kinematic information, obtained during the manipulation process and reasoning about the desired and real positions of the fingertips during the manipulation. This is done taking into account that the desired positions of the fingertips are not physically reachable since they are located in the interior of the manipulated object and therefore they are virtual positions with associated virtual contact points. The proposed approach was satisfactorily validated using three fingers of an anthropomorphic robotic hand (Allegro Hand), with the original fingertips replaced by tactile sensors (WTS-FT). In the experimental validation, several everyday objects with different shapes were successfully manipulated, rotating them without the need of knowing their shape or any other physical property.

Highlights

Dexterous manipulation of objects has been one of the most relevant topics in robotic research during the past years [1]
The problem addressed in this work is the manipulation of unknown objects with a robotic hand equipped with tactile sensors, understanding by an “unknown objects” that object properties like shape, weight and center of mass are not known during the manipulation, that is, the manipulation is done without the knowledge of an object model
The paper has presented a simple but effective approach for the manipulation of unknown object based on tactile information

Summary

Introduction

Dexterous manipulation of objects has been one of the most relevant topics in robotic research during the past years [1]. On the other hand, regarding complementary hardware, vision systems has been used to complement the tactile information in the exploration of unknown objects [37], an regarding complementary software, machine learning approaches has been proposed for the detection of slippage [38], for the object recognition [29], for the adaptation of the grasping motion [39], and for the extraction of manipulation primitives for compliant robot hands [14] In this context, the goal of the approach proposed in this work is the dexterous in-hand manipulation (no need of wrist or arm movements) of an unknown object starting from a given initial grasp and keeping the contact between each finger and the object during the manipulation (i.e., finger gaiting is not applied) while keeping the grasping forces within a desired range and preventing the object from falling.

Problem Statement

Proposed Manipulation Strategy

Hardware Set-up

Experiments

Conclusions