Bence P. Ölveczky

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

This paper finds that using a low-cost quadrupedal hardware platform, using a forward model of the average actuator delay, paired with a time-aware neural network results in robust locomotion, and posit that temporal self-organization may be a general strategy for cost-constrained locomotion.