Multi-Joint Coordinated Motion Planning and Energy Efficiency Optimization of Unitree G1 Robot for Stage Performances
DOI:
https://doi.org/10.54097/ngpkdd57Keywords:
Motion Planning, Multi-Joint Coordination, Energy Optimization, Rotation Matrix, PSO AlgorithmAbstract
To meet the motion planning and energy optimization requirements for the dance performance of the Unitree G1 humanoid robot, this paper systematically constructs mathematical models for four core issues and proposes corresponding optimization strategies. Firstly, a Cartesian coordinate system with the shoulder joint as the origin is established, and the final coordinates of the left arm endpoint are calculated to be (292.4, -84.5, 169.0) millimeters through rotation matrix transformation and D-H parameter verification. The safety of the motor is confirmed by verifying that both joint angles and torque (4.3 N·m) are within the safe threshold range. Then, a fifth-order polynomial interpolation model is adopted to establish the relationship between the joint angle of a single leg and time, determining the total motion time T=5.2 seconds, and identifying t=1.8 seconds as the moment when the rate of change of the knee joint angle is the largest (3.2°/s). Simultaneously, the rotation of the body to the left by 45° is described using Euler angles, and the parametric equation for the arm's reverse circular motion (ω=1.57 rad/s) is established. A leg balance adjustment model based on center of gravity offset compensation is designed to ensure that the center of gravity remains within the support plane. The total energy consumption for all actions is calculated to be 127.0 Wh using the motor power formula P=τω/η. An optimization scheme combining S-curve trajectory smoothing, joint load balancing, and J5 joint constraint control is proposed, which reduces energy consumption to 2.06 Wh (a reduction of 15.36%) while maintaining performance quality. Simulation results and sensitivity analysis confirm that these models exhibit good smoothness, safety, and energy efficiency, providing a reliable theoretical foundation for the actual performance of the robot.
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