RONov 25, 2020

Redundancy Resolution and Disturbance Rejection via Torque Optimization in Hybrid Cable-Driven Robots

arXiv:2011.12457v1
AI Analysis

This work provides a novel solution for redundancy resolution and disturbance rejection in Hybrid Cable-Driven Robots, which could benefit the control and operation of these specific robotic systems.

This paper addresses redundancy resolution and disturbance rejection in Hybrid Cable-Driven Robots (HCDRs) by proposing two torque optimization methods: TOAJ and TOAUJ. The TOAUJ method is presented as the first solution for HCDRs that simultaneously handles redundancy resolution and disturbance rejection.

This paper presents redundancy resolution and disturbance rejection via torque optimization in Hybrid Cable-Driven Robots (HCDRs). To begin with, we initiate a redundant HCDR for nonlinear whole-body system modeling and model reduction. Based on the reduced dynamic model, two new methods are proposed to solve the redundancy resolution problem: joint-space torque optimization for actuated joints (TOAJ) and joint-space torque optimization for actuated and unactuated joints (TOAUJ), and they can be extended to other HCDRs. Compared to the existing approaches, this paper provides the first solution (TOAUJ-based method) for HCDRs that can solve the redundancy resolution problem as well as disturbance rejection. Additionally, this paper develops detailed algorithms targeting TOAJ and TOAUJ implementation. A simple yet effective controller is designed for generated data analysis and validation. Case studies are conducted to evaluate the performance of TOAJ and TOAUJ, and the results suggest the effectiveness of the aforementioned approaches.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes