Christopher Bradley — accepted AI-conference papers

2021

Learning and Planning for Temporally Extended Tasks in Unknown Environments

Christopher Bradley, Adam Pacheck, Gregory J. Stein, Sebastian Castro, Hadas Kress-Gazit, Nicholas Roy

ICRA 2021poster

We propose a novel planning technique for satisfying tasks specified in temporal logic in partially revealed environments. We define high-level actions derived from the environment and the given task itself, and estimate how each action contributes to progress towards completing the task. As the map…

Cited by 26 Source ↗Scholar ↗

2020

Enabling Topological Planning with Monocular Vision

Gregory J. Stein, Christopher Bradley, Victoria Preston, Nicholas Roy

ICRA 2020poster

Topological strategies for navigation meaningfully reduce the space of possible actions available to a robot, allowing use of heuristic priors or learning to enable computationally efficient, intelligent planning. The challenges in estimating structure with monocular SLAM in low texture or highly cl…

Cited by 9 Source ↗Scholar ↗

2018

Learning over Subgoals for Efficient Navigation of Structured, Unknown Environments

Gregory J. Stein, Christopher Bradley, Nicholas Roy

CoRL 2018

We propose a novel technique for efficiently navigating unknown environments over long horizons by learning to predict properties of unknown space. We generate a dynamic action set defined by the current map, factor the Bellman Equation in terms of these actions, and estimate terms, such as the prob

Cited by 0 Source ↗PDF ↗Scholar ↗