5 papers · 1 filter
PrefPI: Preference-Guided Steering into Out-of-Distribution Behaviors
Seungeun Rho, Wontaek Kim, Danfei Xu +1
We present PrefPI (Preference-Guided Policy Iteration), an iterative framework for steering pretrained generative robot policies using only relative preferences over self-generated…
LineRides: Line-Guided Reinforcement Learning for Bicycle Robot Stunts
Seungeun Rho, Shamel Fahmi, Jeonghwan Kim +3
Designing reward functions for agile robotic maneuvers in reinforcement learning remains difficult, and demonstration-based approaches often require reference motions that are unav…
Flip Stunts on Bicycle Robots using Iterative Motion Imitation
Jeonghwan Kim, Shamel Fahmi, Seungeun Rho +2
This work demonstrates a front-flip on bicycle robots via reinforcement learning, particularly by imitating reference motions that are infeasible and imperfect. To address this, we…
Switch4EAI: Leveraging Console Game Platform for Benchmarking Robotic Athletics
Tianyu Li, Jeonghwan Kim, Wontaek Kim +3
Recent advances in whole-body robot control have enabled humanoid and legged robots to execute increasingly agile and coordinated movements. However, standardized benchmarks for ev…
Unsupervised Skill Discovery as Exploration for Learning Agile Locomotion
Seungeun Rho, Kartik Garg, Morgan Byrd +1
Exploration is crucial for enabling legged robots to learn agile locomotion behaviors that can overcome diverse obstacles. However, such exploration is inherently challenging, and…