5 citations · 8 across the 8 of their papers we have counts for
8 papers
CORL-AUV: CFD Oriented Reinforcement Learning for Autonomous Underwater Vehicles
Steven Roche, Milo Van Mooy, Nathan McGuire +3
Precise control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Reinforcement learning (RL) offers rapid co…
Language-Grounded Hierarchical Planning and Execution with Multi-Robot 3D Scene Graphs
Jared Strader, Aaron Ray, Jacob Arkin +11
In this paper, we introduce a multi-robot system that integrates mapping, localization, and task and motion planning (TAMP) enabled by 3D scene graphs to execute complex instructio…
GRAM: Generalization in Deep RL with a Robust Adaptation Module
James Queeney, Xiaoyi Cai, Alexander Schperberg +3
The reliable deployment of deep reinforcement learning in real-world settings requires the ability to generalize across a variety of conditions, including both in-distribution scen…
PIETRA: Physics-Informed Evidential Learning for Traversing Out-of-Distribution Terrain
Xiaoyi Cai, James Queeney, Tong Xu +8
Self-supervised learning is a powerful approach for developing traversability models for off-road navigation, but these models often struggle with inputs unseen during training. Ex…
Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows
Minjae Cho, Jonathan P. How, Chuangchuang Sun
Despite notable successes of Reinforcement Learning (RL), the prevalent use of an online learning paradigm prevents its widespread adoption, especially in hazardous or costly scena…
Look Before You Leap: Socially Acceptable High-Speed Ground Robot Navigation in Crowded Hallways
Lakshay Sharma, Jonathan P. How
To operate safely and efficiently, autonomous warehouse/delivery robots must be able to accomplish tasks while navigating in dynamic environments and handling the large uncertainti…
EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy
Xiaoyi Cai, Siddharth Ancha, Lakshay Sharma +7
Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead of manually designing costs based on terrain features, existing methods learn terra…
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
Dong-Ki Kim, Matthew Riemer, Miao Liu +5
The main challenge of multiagent reinforcement learning is the difficulty of learning useful policies in the presence of other simultaneously learning agents whose changing behavio…