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James (Drew) Bagnell
Research Scientist

Associated center: NREC

Email address: bagnell2@andrew.cmu.edu
Office: NSH 3111
Phone: (412) 681-8669

Mailing address:
National Robotics Engineering Center
10 40th Street
Pittsburgh, PA 15201

For more information, see my personal homepage.

Jump to: Research interests | Keywords | Labs & groups | Projects | Publications

Research interests

I am interested in "closing the loop" on complex systems; that is, I am interested in designing algorithms that allow systems to observe their own operation and improve performance. My belief is that the border land between planning, control and computational learning is particularly rich with research challenges and potential to make real, immediate impact on applications. I'm particularly interested in systems for which we can obtain at best a partial model. To this end, I'm excited about extending research tools that come from information theory, statistics, control theory, statistical physics and optimization.

At the moment, I am particularly focused on two areas in machine learning. First I am working on applications of learning and decision making applied to mobile robotics. Second, I am interested in developing rich, structured probabilistic models that are appropriate for both making and learning decisions.

Research interest keywords

artificial intelligence, control, machine learning, mobile robots, and planning

Current Labs & Groups

Auton Lab - We build practical large-scale deployments of very highly autonomous self-improving systems.
 

Current Projects [Past projects]

Learning Locomotion - Robust planning and control of the quadruped robot "Little Dog" to traverse rough terrain (DARPA sponsored).
Quality of Life Technology Center - QoLT is a unique partnership between Carnegie Mellon and the University of Pittsburgh that brings together a cross-disciplinary team of technologists, clinicians, industry partners, end users, and other stakeholders to create revolutionary technologies that will improve and sustain the quality of life for all people.
Tartan Racing - Carnegie Mellon University is teaming with General Motors to compete in the 2007 DARPA Urban Challenge.
UGCV PerceptOR Integrated - The UPI (UGCV PerceptOR Integrated) program integrates and enhances the results from UGCV and PerceptOR to increase the speed and autonomy of unmanned ground vehicles operating in complex terrain. By combining the inherent mobility of Spinner with advanced perception techniques including the use of learning and prior terrain data, the UPI program stresses system design across vehicle, sensors and software so that the strengths of one component compensate for the weaknesses of another.
Urban Challenge
 

Recent publications [View all 27 publications]

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