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Found 4 papers, 1 papers with code
KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long-Term Trajectory Prediction
Predicting future trajectories of road agents is a critical task for autonomous driving.
Real-Time Tube-Based Non-Gaussian Risk Bounded Motion Planning for Stochastic Nonlinear Systems in Uncertain Environments via Motion Primitives
We consider the motion planning problem for stochastic nonlinear systems in uncertain environments.
Non-Gaussian Uncertainty Minimization Based Control of Stochastic Nonlinear Robotic Systems
In particular, in the provided optimization problem, we use moments and characteristic functions to propagate uncertainties throughout the nonlinear motion model of robotic systems.
Convex Risk Bounded Continuous-Time Trajectory Planning and Tube Design in Uncertain Nonconvex Environments
To address the risk bounded trajectory planning problem, we leverage the notion of risk contours to transform the risk bounded planning problem into a deterministic optimization problem.
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