Home /Research /Research on human-robot collaboration method for parallel robots oriented to segment docking
HRI

Research on human-robot collaboration method for parallel robots oriented to segment docking

Deyuan Sun, Junyi Wang, Zhigang Xu, Jianwen Bao, Han Lü

Year
2024
Citations
3
Access
Open access

Abstract

<title>Abstract</title> In the field of aerospace, large and heavy cabin segments present a significant challenge in assembling space engines. The considerable inertial force of cabin segments’ mass causes unexpected motion during docking, leading to segment collisions and difficulty in ensuring precise engine segment docking. Traditional manual docking utilizes workers' expertise, yet the labor-intensive nature and low productivity are unsuitable for practical applications. Human-robot collaboration can effectively integrate the advantages of humans and robots. Additionally, parallel robots, known for their precision and load-bearing ability, are widely employed in precise assembly tasks under heavy loads. Thus, human-parallel-robot collaboration serves as an excellent solution for these challenges. This paper proposes an easily implementable framework, employing human-parallel-robot collaboration technology for cabin segment docking in production. A fractional-order variable damping admittance control and an inverse dynamics robust controller are suggested to improve the robot's compliance, responsiveness, and trajectory tracking accuracy in collaboration. This allows operators to dynamically adjust the robot's motion in real-time, counterbalancing inertial forces and preventing collisions. Segment docking assembly experiments are conducted utilizing the Stewart platform in this study. The results show that the proposed method enables the robot to quickly respond to interaction forces, ensuring compliance and stable motion accuracy, even under unknown interaction forces.

Keywords

RobotFictitious forceInertial frame of referenceComputer scienceDocking (animal)SimulationControl engineeringEngineeringArtificial intelligence

Related papers

Browse all HRI papers