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Barkour: Benchmarking Animal-level Agility with Quadruped Robots
In the second approach, we distill the specialist skills into a Transformer-based generalist locomotion policy, named Locomotion-Transformer, that can handle various terrains and adjust the robot's gait based on the perceived environment and robot states.
Learning and Adapting Agile Locomotion Skills by Transferring Experience
Legged robots have enormous potential in their range of capabilities, from navigating unstructured terrains to high-speed running.
Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous
We propose hierarchical predictive planning (HPP), a model-based reinforcement learning method for decentralized multiagent rendezvous.
Model-based Reinforcement Learning
reinforcement-learning
+1
Neural Collision Clearance Estimator for Batched Motion Planning
We present a neural network collision checking heuristic, ClearanceNet, and a planning algorithm, CN-RRT.
Long-Range Indoor Navigation with PRM-RL
Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings.
