I am a computer science PhD student
at the University of Texas at Austin. My research interests lie in
spatial reasoning and learning for robots. This work is done in Ben
Kuipers intelligent robotics group. Previously, I was a mathematician
studying Finsler geometry at the University of Alberta.
My research is in artificial intelligence, focusing on the cognitive
development of intelligent robots. I have worked on several methods that
bridge the divide between the representations that robots need for
intelligence (high-level concepts of space, objects and actions) and the
physical devices that robots use for interaction (low-level sensors
and motors).
Bootstrap learning an object ontology My thesis work
examines how a robot can autonomously discover and use objects.
- Bootstrap learning for object discovery
Joseph Modayil and Benjamin Kuipers. In
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04), pages 742--747.
[pdf]
[abstract]
[Earlier symposium version]
 
-
Autonomous shape model learning for object localization and recognition
Joseph Modayil and Benjamin Kuipers. In
IEEE International Conference on Robotics and Automaton (ICRA-06), pages 2991--2996.
[pdf] [abstract]
- Bootstrap learning of foundational representations
Benjamin Kuipers, Patrick Beeson, Joseph Modayil, and Jefferson Provost.
Connection Science, 18(2), June 2006, pages 145-158.
[pdf][abstract][Earlier workshop version]
- Where do actions come from? Autonomous robot learning of objects and actions
Joseph Modayil and Benjamin Kuipers.
In AAAI Spring Symposium Series 2007, Control Mechanisms for Spatial Knowledge Processing in Cognitive / Intelligent Systems.
[pdf][abstract]
- Autonomous Development of a Grounded Object Ontology by a Learning Robot
Joseph Modayil and Benjamin Kuipers.
In the Proceedings of the Twenty-Second Conference on
Artificial Intelligence (AAAI-07).
[pdf][abstract]
- Robot Developmental Learning of an Object Ontology Grounded in Sensorimotor Experience
Joseph Modayil. Doctoral dissertation, Computer Sciences Department, University of Texas at Austin.
[pdf][abstract]
Hybrid mapping techniques
We have created a hybrid topological/metrical robot map builder.
- Local metrical and global topological maps in the Hybrid Spatial Semantic Hierarchy
Benjamin Kuipers, Joseph Modayil, Patrick Beeson, Matt MacMahon, and Francesco Savelli. In
IEEE International Conference on Robotics and Automation (ICRA-04).
[pdf]
[abstract]
- Using the topological skeleton for scalable global metrical map-building
Joseph Modayil, Patrick Beeson and Benjamin Kuipers. In
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04), pages 1530--1536.
[pdf]
[abstract]
 
Safety Maps
Robots need maps to indicate which regions are safe for travel.
- Building local safety maps for a wheelchair robot using vision and lasers
(Best student paper!)
Aniket Murarka, Joseph Modayil, and Benjamin Kuipers. In
Canadian Conference on Computer and Robot Vision (CRV-06).
[pdf]
[abstract]
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