A constrained control-planning strategy for redundant manipulators

TL;DR

This paper introduces a robust, computationally efficient control-planning strategy for redundant manipulators that considers system constraints and environmental factors, demonstrated through real-world experiments with a 7 DOF robot.

Contribution

It proposes a novel interconnected control-planning approach integrating low-level control and high-level planning for complex environments with constraints.

Findings

Effective in real-world scenarios with a 7 DOF manipulator

Computationally efficient for real-time implementation

Successfully handles joint and environmental constraints

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, the estimated dynamic model of the robotic system and the nullspace of the linearized 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 DOF manipulator, we demonstrate the performance of the method in real-world scenarios.