4 papers
MR. POP: Multi-Robot Parallel Optimizing Planner for Almost-Surely Asymptotically Optimal Planning
Chih H. Huang, Roy Xing, Brian Plancher +1
Finding globally optimal paths remains a fundamental challenge in multi-robot motion planning. Despite acceleration of almost-surely asymptotically optimal (a.s.a.o.) planners via…
MPC-Injection: Biasing Off-Policy Locomotion RL Toward Controller-Induced Behavior Basins
Roy Xing, Seyoung Ree, Brian Plancher
Reinforcement learning (RL) for locomotion frequently converges to locally optimal but undeployable behaviors, such as vibrating limbs or scooting on the torso, that maximize retur…
ASCII Art Turns LLMs into VLA Controllers
Yitao Jiang, Roy Xing, Luyang Zhao +3
Vision--Language--Action (VLA) controllers are often built by extending vision--language models (VLMs) with action supervision, relying on multimodal backbones with large data and…
Sample-Based Output-Feedback Navigation with Bearing Measurements
Mahroo Bahreinian, Marc Mitjans, Roy Xing +1
We consider the problem of sample-based feedback-based motion planning from bearing (direction-only) measurements. We build on our previous work that defines a cell decomposition o…