A two-layer system uses multi-rate NMPC to jointly plan contact points and body trajectories for wall-supported bipedal walking in quadrupeds, showing 2.9 times higher simulation success than heuristic MPC on rough terrain.
//arxiv.org/abs/2207.10465
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Integrates iterative learning control with a torque library to enable high-precision adaptive locomotion on bipedal and quadrupedal robots, reducing tracking errors by up to 85% and achieving over 30x faster control rates.
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Multi-Rate Nonlinear Model Predictive Control for Wall-Supported Bipedal Locomotion of Quadrupedal Robots
A two-layer system uses multi-rate NMPC to jointly plan contact points and body trajectories for wall-supported bipedal walking in quadrupeds, showing 2.9 times higher simulation success than heuristic MPC on rough terrain.
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Iteratively Learning Muscle Memory for Legged Robots to Master Adaptive and High Precision Locomotion
Integrates iterative learning control with a torque library to enable high-precision adaptive locomotion on bipedal and quadrupedal robots, reducing tracking errors by up to 85% and achieving over 30x faster control rates.