6 papers
Learning Agile Robotic Locomotion Skills by Imitating Animals
Xue Bin Peng, Erwin Coumans, Tingnan Zhang +3
Reproducing the diverse and agile locomotion skills of animals has been a longstanding challenge in robotics. While manually-designed controllers have been able to emulate many com…
Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous
Rose E. Wang, J. Chase Kew, Dennis Lee +5
Collaboration requires agents to align their goals on the fly. Underlying the human ability to align goals with other agents is their ability to predict the intentions of others an…
Learned Critical Probabilistic Roadmaps for Robotic Motion Planning
Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee +1
Sampling-based motion planning techniques have emerged as an efficient algorithmic paradigm for solving complex motion planning problems. These approaches use a set of probing samp…
Neural Collision Clearance Estimator for Batched Motion Planning
J. Chase Kew, Brian Ichter, Maryam Bandari +2
We present a neural network collision checking heuristic, ClearanceNet, and a planning algorithm, CN-RRT. ClearanceNet learns to predict separation distance (minimum distance betwe…
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…