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Found 4 papers, 2 papers with code
Learning Quadruped Locomotion Using Differentiable Simulation
This work provides several important insights into using differentiable simulations for legged locomotion in the real world.
FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning
Motion trajectories offer reliable references for physics-based motion learning but suffer from sparsity, particularly in regions that lack sufficient data coverage.
Learning Emergent Gaits with Decentralized Phase Oscillators: on the role of Observations, Rewards, and Feedback
We present a minimal phase oscillator model for learning quadrupedal locomotion.
Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Although several studies have explored the use of potential based reward shaping to accelerate learning convergence, most have been limited to grid-worlds and low-dimensional systems, and RL in robotics has predominantly relied on standard forms of reward shaping.
