69 citations · 69 across the 2 of their papers we have counts for
2 papers
cs.LG2025
RANDPOL: Parameter-Efficient End-to-End Quadruped Locomotion via Randomized Policy Learning
Zhuochen Liu, Rahul Jain, Quan Nguyen
Modern learning-based locomotion controllers typically rely on fully trainable deep neural networks with a large number of parameters. This paper studies a different design point f…
cs.RO2021★ 69 cited
Robust High-speed Running for Quadruped Robots via Deep Reinforcement Learning
Guillaume Bellegarda, Yiyu Chen, Zhuochen Liu +1
Deep reinforcement learning has emerged as a popular and powerful way to develop locomotion controllers for quadruped robots. Common approaches have largely focused on learning act…