Task-Based Compliance Control for Bottle Screw Manipulation With a Dual-Arm Robot

In this article, a novel task-based compliance control approach for a dual-arm robot is presented with a bottle screw task. The presented approach aims at overcoming uncertainties from the object model and contact forces during the bottle screw task. A novel framework is proposed to synthesize the task motion planning and compliance control that ensure desired performance of both accuracy and compliant motion. The proposed task-based compliance control approach provides a hierarchical strategy: gross motion planning and fine compliance motion planning. The gross motion planning involves the absolute and relative motion control on a macroscale, while the fine compliance motion planning deals with uncertainties by the compliance control to accomplish a task requiring high precision robustly. A theoretical modeling of the bottle screw task is presented within the proposed framework through the analysis of uncertainties and constraints. The experimental results show that the proposed framework is efficient and robust to operate a set of bottles.

I. Introduction

Bottle screw task is one of the most common daily-life tasks, it is yet to be discussed widely. In previous studies, some researchers focused only on opening a jar, a can, or a bottle. Both Honda's Asimo anthropomorphic robot and Stanford University's PR2 robot attempted the task of opening a bottle cap. But they did not fasten it back, which reduced the complexity of the experiment. One of the challenges for this task is the absence of a widely accepted framework that combines the motion planning and compliance control to guarantee the stability of both accuracy motion and contact forces [1]. In particular, kinematic and contact uncertainties are inevitable and may lead to the failure of the task [2].