
-
Learning Navigation Skills for Legged Robots with Learned Robot Embeddings
Navigation policies are commonly learned on idealized cylinder agents in...
read it
-
Leveraging Forward Model Prediction Error for Learning Control
Learning for model based control can be sample-efficient and generalize ...
read it
-
Model-Based Inverse Reinforcement Learning from Visual Demonstrations
Scaling model-based inverse reinforcement learning (IRL) to real robotic...
read it
-
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion
Hierarchical learning has been successful at learning generalizable loco...
read it
-
Learning State-Dependent Losses for Inverse Dynamics Learning
Being able to quickly adapt to changes in dynamics is paramount in model...
read it
-
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Bayesian optimization (BO) is a popular approach to optimize expensive-t...
read it
-
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm
The recursive Newton-Euler Algorithm (RNEA) is a popular technique in ro...
read it
-
Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning
Learning to locomote to arbitrary goals on hardware remains a challengin...
read it
-
Bayesian Optimization in Variational Latent Spaces with Dynamic Compression
Data-efficiency is crucial for autonomous robots to adapt to new tasks a...
read it
-
Curious iLQR: Resolving Uncertainty in Model-based RL
Curiosity as a means to explore during reinforcement learning problems h...
read it
-
Using Deep Reinforcement Learning to Learn High-Level Policies on the ATRIAS Biped
Learning controllers for bipedal robots is a challenging problem, often ...
read it
-
Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots
Learning for control can acquire controllers for novel robotic tasks, pa...
read it