The Robotics Institute

Carnegie Mellon Robotics Institute

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		J. Andrew (Drew) Bagnell Associate Professor, RI Email:   Mailing address: Carnegie Mellon University Robotics Institute 5000 Forbes Avenue Pittsburgh, PA 15213 Administrative Assistant: Jessica Butterbaugh Affiliated Center(s):  Quality of Life Technology Center (QoLT)  National Robotics Engineering Center (NREC) Personal Homepage

Current Projects [Past Projects]
		Auton Project Research into Autonomous Learning Software Systems
		Learning Locomotion Robust planning and control of the quadruped robot "Little Dog" to traverse rough terrain (DARPA sponsored).
		LIDAR and Vision Sensor Fusion for Autonomous Vehicle Navigation The goal of this project is to investigate methods for combining laser range sensors (i.e., LIDARs) with visual sensors (i.e., video cameras) to improve the capabilities of autonomous vehicles.
		PeepPredict We are applying machine learning techniques to model and compute long-term and short-term trajectories of people in a variety of settings.
		Quality of Life Technology (QoLT) 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. Note: The QoLT Project has been superseded by the QoLT Center.
		Terrain Estimation using Space Carving Kernels This project uses information about the ray extending from the sensor to the sensed surface be used to improve terrain estimation in unstructured environments.
		UGCV PerceptOR Integrated (UPI) 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.