Global navigation-local operation: Pose optimization and multi-sensory guidance strategy for autonomous mobile manipulators

Abstract

This paper presents a novel control method for integrating global navigation and local operation in an autonomous mobile operating system (AMOS). A pose optimization method based on null-space projection is proposed to enable seamless switching between global navigation and local operation. Additionally, a control strategy that combines both visual perception and force feedback for effective guidance during local operations is introduced. Firstly, utilizing projected gradient, the task space is partitioned into primary and null spaces, and secondary task functions are designed to optimize and constrain the pose while preserving the primary task. Secondly, a 2-stage guidance strategy for shaft hole insertion, incorporating visual perception and force control techniques, is presented. This strategy involves visual guidance for point cloud registration and fine adjustment using force sensing. To address transient and steady-state errors in the system, a finite-time prescribed performance super-twisting algorithm (PPSTA) controller is proposed and its stability is proven using Lyapunov theory. Simulation and experimental results validate the effectiveness of the proposed method in achieving both navigation and manipulation tasks for mobile manipulators with high performance and robustness.