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T. N. Mundhenk, C. Ackerman, D. Chung, N. Dhavale, B. Hudson, R. Hirata, E. Pichon, Z. Shi, A. Tsui, L. Itti, Low-cost high-performance mobile robot design utilizing off-the-shelf parts and the Beowulf concept: the Beobot project, In: Proc. SPIE Conference on Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, pp. 293-303, Bellingham, WA:SPIE Press, Oct 2003.
Abstract: Utilizing off the shelf low cost parts, we have constructed a robot that is small, light, powerful and relatively inexpensive (less than USD 3900). The system is constructed around the Beowulf concept of linking multiple discrete computing units into a single cooperative system. The goal of this project is to demonstrate a new robotics platform with sufficient computing resources to run biologically-inspired vision algorithms in real-time. This is accomplished by connecting two dual-CPU embedded PC motherboards using fast gigabit Ethernet. The motherboards contain integrated Firewire, USB and serial connections to handle camera, servomotor, GPS and other miscellaneous inputs/outputs. Computing systems are mounted on a servomechanism-controlled off-the-shelf Off Road RC car. Using the high performance characteristics of the car, the robot can attain relatively high speeds outdoors. The robot is used as a test platform for biologically-inspired as well as traditional robotic algorithms, in outdoor navigation and exploration activities. Leader following using multi blob tracking and segmentation, and navigation using statistical information and decision inference from image spectral information are discussed. The design of the robot is open-source and is constructed in a manner that enhances ease of replication. This is done to facilitate construction and development of mobile robots at research institutions where large financial resources may not be readily available as well as to put robots into the hands of hobbyists and help lead to the next stage in the evolution of robotics, a home hobby robot with potential real world applications.
Themes: Model of Bottom-Up Saliency-Based Visual Attention, Beobots, Computational Modeling, Computer Vision
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