Comprehensive Performance Optimization of a New Reconfigurable Two-Wheeled Self-Balancing Robot Based on Virtual Equivalent Parallel Mechanism
24 PagesPosted: 10 Jul 2022
Hongyan Tang
Fudan University
Dan Zhang
York University
James M. Zhang
McMaster University
Abstract
Two-wheeled self-balancing robot (TWSBR) is a mobile robot with a widely application in security, rescue, entertainment and other fields. To make the robot obtain a larger range of the controllable inclination angle, a reconfigurable mechanism of moment of inertia is designed for the TWSBR, and the energy consumption of the reconfigurable mechanism is reduced by a gravity compensation mechanism. This paper constructs a virtual equivalent parallel mechanism (VEPM) to model the robot-ground system combining the robot and the ground. The kinematics, dynamic model and performance indexes of the VEPM are solved based on the vector method, the Lagrangian dynamics and the screw theory. Then, the dimensions of the mechanism are optimized based on the comprehensive performance analysis. Finally, the effectiveness of the optimization algorithm and gravity compensation mechanism is verified through simulation and motion experiments. The performance analysis and optimal design approaches proposed in this paper have positive significance for the systematic modeling and optimal design of two-wheeled and two-legged robots.
Keywords: parallel mechanism, self-balancing robot, gravity compensation mechanism, performance optimization
Suggested Citation:Suggested Citation
Hongyan Tang
Fudan University (email )
Beijing West District Baiyun Load 10th
Shanghai, 100045
China
Dan Zhang (Contact Author)
York University (email )
James M. Zhang
McMaster University (email )
1280 Main Street West
Hamilton
Canada
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