Search Results for author:
Found 6 papers, 4 papers with code
Adaptive Control Strategy for Quadruped Robots in Actuator Degradation Scenarios
Quadruped robots have strong adaptability to extreme environments but may also experience faults.
Privileged Knowledge Distillation for Sim-to-Real Policy Generalization
In this paper, we propose a novel single-stage privileged knowledge distillation method called the Historical Information Bottleneck (HIB) to narrow the sim-to-real gap.
Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer
Deep reinforcement learning has recently emerged as an appealing alternative for legged locomotion over multiple terrains by training a policy in physical simulation and then transferring it to the real world (i. e., sim-to-real transfer).
A Survey on Model-based Reinforcement Learning
In this survey, we take a review of MBRL with a focus on the recent progress in deep RL.
On Effective Scheduling of Model-based Reinforcement Learning
Model-based reinforcement learning has attracted wide attention due to its superior sample efficiency.
Bidirectional Model-based Policy Optimization
Model-based reinforcement learning approaches leverage a forward dynamics model to support planning and decision making, which, however, may fail catastrophically if the model is inaccurate.
