5 papers
Parameter-Robust MPPI for Safe Online Learning of Unknown Parameters
Matti Vahs, Jaeyoun Choi, Niklas Schmid +2
Robots deployed in dynamic environments must remain safe even when key physical parameters are uncertain or change over time. We propose Parameter-Robust Model Predictive Path Inte…
BURNS: Backward Underapproximate Reachability for Neural-Feedback-Loop Systems
Chelsea Sidrane, Jana Tumova
Learning-enabled planning and control algorithms are increasingly popular, but they often lack rigorous guarantees of performance or safety. We introduce an algorithm for computing…
Risk-Aware Robot Control in Dynamic Environments Using Belief Control Barrier Functions
Shaohang Han, Matti Vahs, Jana Tumova
Ensuring safety for autonomous robots operating in dynamic environments can be challenging due to factors such as unmodeled dynamics, noisy sensor measurements, and partial observa…
Finding Control Invariant Sets via Lipschitz Constants of Linear Programs
Matti Vahs, Shaohang Han, Jana Tumova
Control invariant sets play an important role in safety-critical control and find broad application in numerous fields such as obstacle avoidance for mobile robots. However, findin…
CageCoOpt: Enhancing Manipulation Robustness through Caging-Guided Morphology and Policy Co-Optimization
Yifei Dong, Shaohang Han, Xianyi Cheng +5
Uncertainties in contact dynamics and object geometry remain significant barriers to robust robotic manipulation. Caging mitigates these uncertainties by constraining an object's m…