1. SENSOR FUSION LABORATORY Thad Roppel, Associate Professor AU Electrical and Computer Engineering Dept. troppel@eng.auburn.edu EXAMPLES Distributed networks of semi-autonomous vehicles Biomimetics – imitating animal sensorimotor behaviors Chemical sensor arrays – “artificial nose” Infrared / Millimeter wave radar for vehicle detection and identification MISSION: Study the benefits of using simultaneous information from multiple sensors to probe the environment.

2. SENSOR FUSION LABORATORY Problem Complexity: Human vs. Machine HUMAN MACHINE EASY HARD EASY HARD Maximum Potential Benefit Object recognition Extraction of Relevant Features from Sensor Arrays Linguistics Arithmetic Logic Thresholding Tallying Judging

3. Personnel and Publications Current Students Rama Narendran (PhD): Biomimetic Simulations of Organized Machine Behavior Arun Raghunathan (MS): Autonomous rovers Adam Ray (MS): Development system for cooperative robotics research Four undergraduates working in the area of cooperative machines REPRESENTATIVE RECENT PUBLICATIONS D. M. Wilson, T. Roppel, and R. Kalim, "Aggregation of Sensory Input for Robust Performance in Chemical Sensing Microsystems," Sensors and Actuators B, 64(1–3), 107-117, June 2000. T. Roppel and D. M. Wilson, "Biologically-Inspired Pattern Recognition for Odor Detection," Pattern Recognition Letters, 21(3), 213–219, March 2000. D. M. Wilson, K. Dunman, T. Roppel, and R. Kalim, "Rank Extraction in Tin-Oxide Sensor Arrays," Sensors and Actuators B, 62(3), 199-210, April 2000. T. Roppel, R. Kalim, and D. Wilson, "Sensory Plane Analog-VLSI for Interfacing Sensor Arrays to Neural Networks, " Virtual Intelligence and Dynamic Neural Networks VI-DYNN '98, Stockholm, Sweden, June 22-26, 1998.

4. Summary of Selected Projects IR / MMW DATA FUSION (AFOSR): Improved identification of military vehicles from aerial scenes using neural networks applied to co-boresighted IR and MMW radar sensors. Chemical Sensor Arrays (DARPA): Improved identification and detection of chemical plumes in non-laboratory conditions. Biomimetics: Learn sensor fusion from animals. Apply this to flying a drone to target using onboard video Robotic Networks: Build cooperative human / robotic networks with distributed, redundant C 3 I capability. Use optic flow to replace GPS for navigation.