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 reconfigurable mechanism enables the TWSBR to stand up, step up and surmount obstacles. 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.
This paper presents and investigates a new three-rotation (3R) parallel compliant mechanism that uses compliant rods to achieve three rotations. The mechanism is designed for use in pointing devices or as a spatial parallel manipulator. The mobility analysis is based on the Cosserat rod model and Lagrangian dynamics equations. The dynamics equations are then effectively solved using the back-propagation neural network and chaos-enhanced accelerated particle swarm optimization. After studying the mobility of the moving platform, a simplified model is proposed and used for kinematic analysis. The analysis of motion includes discussions on forward kinematics, inverse kinematics, singularities, and the workspace. Furthermore, experiments with a prototype are conducted to verify the accuracy and stability of the mobility analysis and the simplified model.
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