6 papers
FARO: Feasibility-Aware Robot Motion Optimization
Michal Ciebielski, Shafeef Omar, Aaron Johnson +1
Fast planning of novel behaviors in unseen scenarios remains a fundamental challenge in robotics. The high-dimensional, hybrid, and underactuated nature of humanoid loco-manipulati…
SURE: Safe Uncertainty-Aware Robot-Environment Interaction using Trajectory Optimization
Zhuocheng Zhang, Haizhou Zhao, Xudong Sun +2
Robotic tasks involving contact interactions pose significant challenges for trajectory optimization due to discontinuous dynamics. Conventional formulations typically assume deter…
Shield-Loco: Shielding Locomotion Policies with Predictive Safety Filtering
Aditya Shirwatkar, Sebastian Sanokowski, Shishir Kolathaya +2
Reinforcement learning (RL) policies enable dynamic legged locomotion but lack mechanisms to avoid violations of safety constraints that are absent during training. Large-scale off…
MotionDisco: Motion Discovery for Extreme Humanoid Loco-Manipulation
Ilyass Taouil, Michal Ciebelski, Shafeef Omar +4
We present MotionDisco, a framework that discovers contact-rich, long-horizon humanoid loco-manipulation motions from scratch, without relying on teleoperation or motion retargetin…
Asynchronous Distributed Multi-Robot Motion Planning Under Imperfect Communication
Ardalan Tajbakhsh, Augustinos Saravanos, James Zhu +3
This paper addresses the challenge of coordinating multi-robot systems under realistic communication delays using distributed optimization. We focus on consensus ADMM as a scalable…
How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints
Kensuke Nakamura, Arun L. Bishop, Steven Man +3
Latent safety filters extend Hamilton-Jacobi (HJ) reachability to operate on latent state representations and dynamics learned directly from high-dimensional observations, enabling…