2 citations · 4 across the 8 of their papers we have counts for
8 papers · 1 filter
Non-Gaussian Risk Bounded Trajectory Optimization for Stochastic Nonlinear Systems in Uncertain Environments
Weiqiao Han, Ashkan Jasour, Brian Williams
We address the risk bounded trajectory optimization problem of stochastic nonlinear robotic systems. More precisely, we consider the motion planning problem in which the robot has…
HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling
Xin Huang, Guy Rosman, Igor Gilitschenski +4
Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicti…
Real-Time Risk-Bounded Tube-Based Trajectory Safety Verification
Ashkan Jasour, Weiqiao Han, Brian Williams
In this paper, we address the real-time risk-bounded safety verification problem of continuous-time state trajectories of autonomous systems in the presence of uncertain time-varyi…
Convex Risk Bounded Continuous-Time Trajectory Planning in Uncertain Nonconvex Environments
Ashkan Jasour, Weiqiao Han, Brian Williams
In this paper, we address the trajectory planning problem in uncertain nonconvex static and dynamic environments that contain obstacles with probabilistic location, size, and geome…
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…
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…