226 citations · 1k across the 102 of their papers we have counts for
5 papers · 1 filter
Simulator Predictive Control: Using Learned Task Representations and MPC for Zero-Shot Generalization and Sequencing
Zhanpeng He, Ryan Julian, Eric Heiden +5
Simulation-to-real transfer is an important strategy for making reinforcement learning practical with real robots. Successful sim-to-real transfer systems have difficulty producing…
Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills
Hejia Zhang, Eric Heiden, Stefanos Nikolaidis +2
Personal robots assisting humans must perform complex manipulation tasks that are typically difficult to specify in traditional motion planning pipelines, where multiple objectives…
Scaling simulation-to-real transfer by learning composable robot skills
Ryan Julian, Eric Heiden, Zhanpeng He +5
We present a novel solution to the problem of simulation-to-real transfer, which builds on recent advances in robot skill decomposition. Rather than focusing on minimizing the simu…
Region Growing Curriculum Generation for Reinforcement Learning
Artem Molchanov, Karol Hausman, Stan Birchfield +1
Learning a policy capable of moving an agent between any two states in the environment is important for many robotics problems involving navigation and manipulation. Due to the spa…
Planning Safe Paths through Hazardous Environments
Chris Denniston, Thomas R. Krogstad, Stephanie Kemna +1
Autonomous underwater vehicles (AUVs) are robotic platforms that are commonly used to map the sea floor, for example for benthic surveys or for naval mine countermeasures (MCM) ope…