A Hybrid Motion Optimization Framework for the Humanoid Upper-Body Robot: Safe and Dexterous Object Carrying

IF 4.6 2区计算机科学 Q2 ROBOTICS

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI:10.1109/LRA.2025.3546091

Zhaoyang Chen;Kang Min;Xinyang Fan;Fenglei Ni;Hong Liu

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引用次数: 0

Abstract

In this letter, a novel hybrid motion optimization framework is proposed for a humanoid upper-body robot with two 7-DOF arms and a 2-DOF waist, to flexibly and safely carry objects in constrained and dynamic environments. The framework consists of trilayer interconnected optimization, which is dedicated to planning the optimal carrying configuration, waist-arm motion trajectory, and dual-arm nullspace trajectory, respectively. The top layer finds the most dexterous waist-arm carrying configuration that satisfies environmental constraints, which is achieved by the effective integration of the multi-objective evolutionary algorithm (EA), the proposed optimal manipulation index, and the parameterization method. The middle layer applies a non-linear optimization method to plan collision-free trajectory that connects the initial and optimal carrying configuration. The bottom layer is achieved by equipping the top layer with elite reproduction operator strategy and adaptive evolution space strategy, generating dual-arm nullspace trajectory in real-time for dynamic obstacle avoidance. The various carrying experiments demonstrate the effectiveness of the proposed framework.

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来源期刊

IEEE Robotics and Automation Letters Computer Science-Computer Science Applications

CiteScore

9.60

自引率

15.40%

发文量

1428

期刊介绍： The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.