I am an Assistant Professor of Computer Science at George Mason University where I run the Robotic Anticipatory Intelligence & Learning (RAIL) Group. Our research, at the intersection of robotics and machine learning, is centered around developing representations that allow robots to better understand the impact of their actions, so that they may plan quickly and intelligently in a dynamic and uncertain world.
Summer 2024 The RAIL Group is delighted to be hosting four high school summer student interns through the George Mason University ASSIP program. Welcome to the lab!
August 27 2023 The lab presented a paper at IEEE CASE, a collaboration with Prof. Erion Plaku, on effective dynamically feasible navigation in partially mapped environments.
May 2023 The lab presented two papers at ICRA 2023.
November 2021 Our paper Generating High-Quality Explanations for Navigation in Partially-Revealed Environments was accepted for a poster presentation at NeurIPS 2021. Video here!
September 2020 I gave a 5 minute lightning talk at the George Mason CS Research Day. Video here!
Fall 2020 I will be joining the Department of Computer Science at George Mason University as an Assistant Professor.
Yimeng Li, Arnab Debnath, Gregory J. Stein, and Jana Kosecka. “Learning-augmented model-based planning for visual exploration.” In: International Conference on Intelligent Robots and Systems (IROS). 2023. paper. show bibtex
@inproceedings{li2023modelexplore,
author = {Yimeng Li and Arnab Debnath and Gregory J. Stein and Jana
Kosecka},
title = {Learning-augmented model-based planning for
visual exploration},
booktitle = {International Conference on Intelligent Robots
and Systems (IROS)},
year = {2023},
note = {in press},
}
Raihan Islam Arnob and Gregory J. Stein. “Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local Information.” In: International Conference on Intelligent Robots and Systems (IROS). 2023. paper, blog post. show bibtex
@inproceedings{arnob2023lspgnn,
title = {Improving Reliable Navigation under Uncertainty via
Predictions Informed by Non-Local Information},
author = {Arnob, Raihan Islam and Stein, Gregory J.},
booktitle = {International Conference on Intelligent Robots
and Systems (IROS)},
year = {2023},
note = {in press},
}
Abhishek Paudel and Gregory J. Stein. “Data-Efficient Policy Selection for Navigation in Partial Maps via Subgoal-Based Abstraction.” In: International Conference on Intelligent Robots and Systems (IROS). 2023. paper, blog post. show bibtex
@inproceedings{paudel2023selection,
title = {Data-Efficient Policy Selection for Navigation in
Partial Maps via Subgoal-Based Abstraction},
author = {Paudel, Abhishek and Stein, Gregory J.},
booktitle = {International Conference on Intelligent Robots
and Systems (IROS)},
year = {2023},
note = {in press},
}
Abhish Khanal, Hoang-Dung Bui, Gregory J. Stein, Erion Plaku: “Guided Sampling-Based Motion Planning with Dynamics in Unknown Environments.” In: International Conference on Automation Science and Engineering (CASE). 2023. paper. show bibtex
@inproceedings{khanal2023guided,
title = {Guided Sampling-Based Motion Planning with Dynamics
in Unknown Environments},
author = {Khanal, Abhish and Bui, Hoang-Dung and Stein, Gregory J. and Plaku, Erion},
booktitle = {International Conference on Automation Science
and Engineering (CASE)},
year = {2023},
note = {in press},
}
Roshan Dhakal, Md Ridwan Hossain Talukder, Gregory J. Stein. “Anticipatory Planning: Improving Long-Lived Planning by Estimating Expected Cost of Future Tasks.” In: International Conference on Robotics and Automation (ICRA). 2023. paper. show bibtex
@inproceedings{dhakal2023anticipatory,
title = {Anticipatory Planning: Improving Long-Lived Planning
by Estimating Expected Cost of Future Tasks},
author = {Dhakal, Roshan and Talukder, Md Ridwan Hossain
and Stein, Gregory J.},
booktitle = {International Conference on Robotics and Automation (ICRA)},
pages = {11538--11545},
year = {2023},
}
Abhish Khanal and Gregory J. Stein. “Learning Augmented, Multi-Robot Long-Horizon Navigation in Partially Mapped Environments.” In: International Conference on Robotics and Automation (ICRA). 2023. paper. show bibtex
@inproceedings{khanal2023mrlsp,
title = {Learning Augmented, Multi-Robot Long-Horizon Navigation in
Partially Mapped Environments},
author = {Khanal, Abhish and Stein, Gregory J.},
booktitle = {International Conference on Robotics and Automation (ICRA)},
pages = {10167--10173},
year = {2023},
}
Gregory J. Stein “Generating High-Quality Explanations for Navigation in Partially-Revealed Environments.” In: Advances in Neural Information Processing Systems (NeurIPS). 2021. paper, talk (13 min), GitHub, blog post. show bibtex
@inproceedings{stein2021xailsp,
title = {Generating High-Quality Explanations for Navigation
in Partially-Revealed Environments},
author = {Gregory J. Stein},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
pages = {17493--17506},
year = {2021},
keywords = {explainability; planning under uncertainty;
subgoal-based planning; interpretable-by-design},
}
Christopher Bradley, Adam Pacheck, Gregory J. Stein, Sebastian Castro, Hadas Kress-Gazit, and Nicholas Roy. “Learning and Planning for Temporally Extended Tasks in Unknown Environments.” In: International Conference on Robotics and Automation (ICRA). 2021. paper, talk (3 min). show bibtex
@inproceedings{bradley2021potlp,
title = {Learning and Planning for Temporally Extended Tasks in Unknown
Environments},
author = {Christopher Bradley and Adam Pacheck and Gregory J. Stein and
Sebastian Castro and Hadas Kress-Gazit and Nicholas Roy},
booktitle = {International Conference on Robotics and Automation (ICRA)},
pages = {4830--4836},
year = {2021},
}
Gregory J. Stein, Christopher Bradley, and Nicholas Roy. “Learning over Subgoals for Efficient Navigation of Structured, Unknown Environments”. In: Conference on Robot Learning (CoRL). 2018. paper, talk (14 min). show bibtex
@inproceedings{stein2018subgoal,
author = {Stein, Gregory J. and Bradley, Christopher and Roy, Nicholas},
title = {Learning over Subgoals for Efficient Navigation of Structured,
Unknown Environments},
booktitle = {Conference on Robot Learning (CoRL)},
pages = {213--222},
year = {2018},
}
Best Paper Finalist at CoRL 2018; Best Oral Presentation at CoRL 2018.Best Paper Finalist at CoRL 2018; Best Oral Presentation at CoRL 2018.
[Workflow & Process] A proof-of-concept for automated running of experiments and automatically including results and statistics in a LaTeX PDF via Make.
[Research] We improve reliable, long-horizon, goal-directed navigation in partially-mapped environments by using non- locally available information to predict the goodness of temporally-extended actions that enter unseen space.
[Research] We present a fast and reliable policy selection approach for navigation in partial maps that leverages information collected during deployment to introspect the behavior of alternative policies without deployment.
[Communication & Learning] I recently asked my students to prep Pecha Kucha-style presentations—18 slides that auto-advance every 20 seconds—and then told them to present each other’s slides, a fun and fantastic (if chaotic) way to improve slide quality.
[Workflow & Process] This guide aims to outline my strategies to encourage idea generation, essential for long-term research progress, through a habit of regular writing.
[Workflow & Process] Even research code benefits greatly from automated testing. My approach to getting started: if you need to write additional code to verify that some functionality is working, that additional code should be written as a test.
[Research] We generate explanations of a robot agent’s behavior as it navigates through a partially-revealed environment, expressed in terms of changes to its predictions about what lies in unseen space. Blog post accompanying our NeurIPS 2021 paper.
[Workflow & Process] I’ve started to think of expectation management as a part of self-care, and I try to think of myself as an other. As such, I try to underpromise and overdeliver to my future self.
[Workflow & Process] I try to make sure that my tasks are both easy to start making progress towards and have clear completion criteria, essential criteria for making sure they get done.
[Communication & Learning] Looking at the in-development work of others pulls back the curtain and reveals insight into the thought process of other researchers. Reviews are a largely-untapped pedagogical resource.
[Workflow & Process] All code in my research group is run exclusively inside Docker containers, helping us develop more quickly and share code with ease.
[Communication & Learning] One communication pitfall I often see is that many researchers will take figures from their papers and paste them into their slides. Here, I provide some tips for tailoring your figures to talks.
[Research] Using DeepMind’s AlphaZero AI to solve real problems will require a change in the way computers represent and think about the world. In this post, we discuss how abstract models of the world can be used for better AI decision making and discuss recent work of ours that proposes such a model for the task of navigation.