3 citations · 3 across the 5 of their papers we have counts for
8 papers · 1 filter
Learning-Based Measurement-Robust Control Barrier Functions for Obstacle Avoidance under State Estimation Error
Nicholas Rober, Yixuan Jia, Jonathan P. How
Safety filters are an effective tool for enforcing constraints in safety-critical systems, but most existing methods assume perfect state information, which is rarely available in…
PRISM: Efficient and Locally Optimal Probabilistic Planning with Reachability Guarantees
Alex Rose, Christopher Jewison, Jonathan P. How
Belief-space planning under motion uncertainty and state and control constraints remains a fundamental challenge, largely due to the difficulty of establishing reachability guarant…
Robust Sampling-Based Covariance Steering for Aerocapture Guidance
Alex Rose, Christopher Jewison, Jonathan P. How
Aerocapture is a maneuver where a spacecraft dives through the atmosphere of a planet or moon to reduce its velocity and prepare for orbital insertion. Aerocapture allows for highe…
A Forward Reachability Perspective on Control Barrier Functions and Discount Factors in Reachability Analysis
Jason J. Choi, Donggun Lee, Boyang Li +4
Control invariant sets are crucial for various methods that aim to design safe control policies for systems whose state constraints must be satisfied over an indefinite time horizo…
GUARDIAN: Safety Filtering for Systems with Perception Models Subject to Adversarial Attacks
Nicholas Rober, Alex Rose, Jonathan P. How
Safety filtering is an effective method for enforcing constraints in safety-critical systems, but existing methods typically assume perfect state information. This limitation is es…
Efficient Probabilistic Planning with Maximum-Coverage Distributionally Robust Backward Reachable Trees
Alex Rose, Naman Aggarwal, Christopher Jewison +1
This paper presents a new multi-query motion planning algorithm for linear Gaussian systems with the goal of reaching a Euclidean ball with high probability. We develop a new formu…