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About this paper
Vyacheslav Kovalev, Ekaterina Chaikovskaia, Egor Davydenko, Roman Gorbachev
A trajectory-based actuator identification method uses differentiable simulation to match real-robot motion data without torque sensors. This approach improves the accuracy of simulated actuator behavior, leading to a 46% increase in travel distance and a 75% reduction in rotational deviation for policies deployed on a physical robot.
Key insights
- Identifying actuator dynamics directly from dynamic motion trajectories substantially improves fidelity compared to models trained on static or steady-state torque data from test stands.
- Differentiable simulation allows for efficient, gradient-based optimization of complex actuator parameters, overcoming sample inefficiency and convergence challenges of gradient-free methods.
- A system-level approach to actuator modeling, capturing the combined effects of electrical, mechanical, and internal control dynamics, is effective for enhancing high-level robot control.
Summary by alphaXiv.
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