Sensorless Pose Determination Using Randomized Action Sequences.

Pragna Mannam,Alexander Volkov,Matthew T Mason,Gregory Chirikjian,Robert Paolini

doi:10.3390/e21020154

Abstract

This paper is a study of 2D manipulation without sensing and planning, by exploring the effects of unplanned randomized action sequences on 2D object pose uncertainty. Our approach follows the work of Erdmann and Mason’s sensorless reorienting of an object into a completely determined pose, regardless of its initial pose. While Erdmann and Mason proposed a method using Newtonian mechanics, this paper shows that under some circumstances, a long enough sequence of random actions will also converge toward a determined final pose of the object. This is verified through several simulation and real robot experiments where randomized action sequences are shown to reduce entropy of the object pose distribution. The effects of varying object shapes, action sequences, and surface friction are also explored.

Highlights

Robots are envisioned to manipulate and interact with objects in unscripted environments and accomplish a diverse set of tasks
We explore a novel pose uncertainty reduction technique based on executing randomized sequence of actions
We show that the Kruskal effect applies for any random sequence to mostly or completely reduce object pose uncertainty

Summary

Introduction

Robots are envisioned to manipulate and interact with objects in unscripted environments and accomplish a diverse set of tasks. Reducing object pose uncertainty is necessary for successful task execution. There are natural ways to reduce pose uncertainty including the addition of physical constraints, relative positioning to a known object’s pose, and actively sensing the desired object’s pose. We explore a novel pose uncertainty reduction technique based on executing randomized sequence of actions. We evaluate our proposed pose uncertainty reduction technique on parts orienting, an industrial automation task. Reducing task state uncertainty in parts orienting systems is an important part of factory automation, especially product assembly. The problem is to take parts in a disorganized jumble and to present them one at a time in a predictable pose. Most industrial solutions involve a part-specific mechanical design. One goal of parts-orienting research is to avoid part-specific mechanical designs, reducing the time required to develop the automation for a new or redesigned product

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