A constrained control-planning strategy for redundant manipulators

Corina Barbalata · Ram Vasudevan · Matthew Johnson-Roberson

Figure 1: Robot working in a cluttered environment in close proximity to people: the Fetch robot [3] reaching for the emergency button, ensuring minimum joint movement to not harm humans in a collaborative environment. — FIGURE FROM THE PAPER

TL;DR

A computationally efficient controller-planner for redundant arms keeps joints within limits, and was tested on a real 7-DOF manipulator.

BRIEF

Robot arms with extra joints can reach a goal in many ways, which helps in cluttered spaces but makes it hard to respect joint limits and environmental constraints. This work links low-level control with high-level path planning. An adaptive control rule, an efficient estimate of the arm's dynamics, and the nullspace of the constraints together generate paths the platform can actually follow. Because it is computationally efficient, it ran on a real 7-DOF arm, where experiments showed the arm staying within joint limits.

Abstract

This paper presents an interconnected control-planning strategy for redundant manipulators, subject to system and environmental constraints. The method incorporates low-level control characteristics and high-level planning components into a robust strategy for manipulators acting in complex environments, subject to joint limits. This strategy is formulated using an adaptive control rule, a computational efficient estimation of the robot’s mathematical model and the nullspace of the constraints. A path is generated that takes into account the capabilities of the platform. The proposed method is computationally efficient, enabling its implementation on a real multi-body robotic system. Through experimental results with a 7 degree-of-freedom (DOF) manipulator, we demonstrate the performance of the method in real-world scenarios.