2 papers
cs.RO2025
Flow-based Domain Randomization for Learning and Sequencing Robotic Skills
Aidan Curtis, Eric Li, Michael Noseworthy +5
Domain randomization in reinforcement learning is an established technique for increasing the robustness of control policies trained in simulation. By randomizing environment prope…
cs.RO2024
Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness
Aidan Curtis, George Matheos, Nishad Gothoskar +4
Integrated task and motion planning (TAMP) has proven to be a valuable approach to generalizable long-horizon robotic manipulation and navigation problems. However, the typical TAM…