5 papers
Scaling Online Exploration for Robot Agents
Runhan Huang, Xiangcheng Zhang, Haoyu Chen +17
Robot learning has advanced by scaling demonstration datasets and model capacity; however, deploying a new robot embodiment or task typically necessitates a dedicated teleoperation…
Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers
Thomas Cohn, Seiji Shaw, Harel Biggie +3
Planning trajectories for robot manipulators under kinematic equality constraints restricts feasible motions to a measure-zero submanifold of the configuration space, requiring spe…
Autonomous Search for Sparsely Distributed Visual Phenomena through Environmental Context Modeling
Eric Chen, Travis Manderson, Nare Karapetyan +3
Autonomous underwater vehicles (AUVs) are increasingly used to survey coral reefs, yet efficiently locating specific coral species of interest remains difficult: target species are…
Toward Learning POMDPs Beyond Full-Rank Actions and State Observability
Seiji Shaw, Travis Manderson, Chad Kessens +1
We are interested in enabling autonomous agents to learn and reason about systems with hidden states, such as locking mechanisms. We cast this problem as learning the parameters of…
Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation
Siddharth Ancha, Sunshine Jiang, Travis Manderson +4
In order to navigate safely and reliably in off-road and unstructured environments, robots must detect anomalies that are out-of-distribution (OOD) with respect to the training dat…