Search Results
Gaussian Process Constraint Learning for Scalable Safe Motion Planning from Demonstrations
Gaussian Process Constraint Learning for Scalable Chance-Constrained Motion Planning
Motion Planning with Graph-Based Trajectories and Gaussian Process Inference
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs
Learning from demonstration with model-based Gaussian process
Task-Motion Planning for Safe and Efficient Urban Driving
L4DC 2020 presentation by Mona Buisson-Fenet, Actively Learning Gaussian Process Dynamics
Prediction of Reward Functions for Deep Reinforcement Learning via Gaussian Process Regression
Gaussian Random Paths for Real-Time Motion Planning
Topological Belief Space Planning
Johannes Wiebe: A robust approach to warped Gaussian process-constrained optimization
Reactive motion planning for a redundant mobile manipulation
