1 citations · 1 across the 8 of their papers we have counts for
8 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…
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…
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…
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…
Path Integral Control for Hybrid Dynamical Systems
Hongzhe Yu, Diana Frias Franco, Aaron M. Johnson +1
This work introduces a novel paradigm for solving optimal control problems for hybrid dynamical systems under uncertainties. Robotic systems having contact with the environment can…
Optimal Covariance Steering of Linear Stochastic Systems with Hybrid Transitions
Hongzhe Yu, Diana Frias Franco, Aaron M. Johnson +1
This work addresses the problem of optimally steering the state covariance of a linear stochastic system from an initial to a target, subject to hybrid transitions. The nonlinear a…