11 citations · 14 across the 4 of their papers we have counts for
12 papers
Fast Risk Assessment for Autonomous Vehicles Using Learned Models of Agent Futures
Allen Wang, Xin Huang, Ashkan Jasour +1
This paper presents fast non-sampling based methods to assess the risk of trajectories for autonomous vehicles when probabilistic predictions of other agents' futures are generated…
Moment State Dynamical Systems for Nonlinear Chance-Constrained Motion Planning
Allen Wang, Ashkan Jasour, Brian Williams
Chance-constrained motion planning requires uncertainty in dynamics to be propagated into uncertainty in state. When nonlinear models are used, Gaussian assumptions on the state di…
Provably Safe Trajectory Optimization in the Presence of Uncertain Convex Obstacles
Charles Dawson, Ashkan Jasour, Andreas Hofmann +1
Real-world environments are inherently uncertain, and to operate safely in these environments robots must be able to plan around this uncertainty. In the context of motion planning…
Fast Certification of Collision Probability Bounds with Uncertain Convex Obstacles
Charles Dawson, Andreas Hofmann, Brian Williams
To operate reactively in uncertain environments, robots need to be able to quickly estimate the risk that they will collide with their environment. This ability is important for bo…
Non-Gaussian Chance-Constrained Trajectory Planning for Autonomous Vehicles under Agent Uncertainty
Allen Wang, Ashkan Jasour, Brian Williams
Agent behavior is arguably the greatest source of uncertainty in trajectory planning for autonomous vehicles. This problem has motivated significant amounts of work in the behavior…
Sequential Chance Optimization For Flow-Tube Based Control Of Probabilistic Nonlinear Systems
Ashkan Jasour, Brian Williams
In this paper, we address the problem of closed-loop control of nonlinear dynamical systems subjected to probabilistic uncertainties. More precisely, we design time-varying polynom…