5 papers · 1 filter
RL-RRT: Kinodynamic Motion Planning via Learning Reachability Estimators from RL Policies
Hao-Tien Lewis Chiang, Jasmine Hsu, Marek Fiser +2
This paper addresses two challenges facing sampling-based kinodynamic motion planning: a way to identify good candidate states for local transitions and the subsequent computationa…
Long Range Neural Navigation Policies for the Real World
Ayzaan Wahid, Alexander Toshev, Marek Fiser +1
Learned Neural Network based policies have shown promising results for robot navigation. However, most of these approaches fall short of being used on a real robot due to the exten…
Long-Range Indoor Navigation with PRM-RL
Anthony Francis, Aleksandra Faust, Hao-Tien Lewis Chiang +4
Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings. We achieve this wi…
Learning Navigation Behaviors End-to-End with AutoRL
Hao-Tien Lewis Chiang, Aleksandra Faust, Marek Fiser +1
We learn end-to-end point-to-point and path-following navigation behaviors that avoid moving obstacles. These policies receive noisy lidar observations and output robot linear and…
FollowNet: Robot Navigation by Following Natural Language Directions with Deep Reinforcement Learning
Pararth Shah, Marek Fiser, Aleksandra Faust +2
Understanding and following directions provided by humans can enable robots to navigate effectively in unknown situations. We present FollowNet, an end-to-end differentiable neural…