Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automating the Design of SOCs Using Cores
IEEE Design & Test
ViperRoos: Developing a Low Cost Local Vision Team for the Small Size League
RoboCup 2001: Robot Soccer World Cup V
Exploring artificial intelligence in the new millennium
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
A Real-time Image Recognition System for Tiny Autonomous Mobile Robots
RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
A Miniature Stereo Vision Machine (MSVM-III) for Dense Disparity Mapping
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Video-rate stereo depth measurement on programmable hardware
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Localization methods for a mobile robot in urban environments
IEEE Transactions on Robotics
FPGA-based real-time optical-flow system
IEEE Transactions on Circuits and Systems for Video Technology
EURASIP Journal on Advances in Signal Processing
Parallel processor for 3D recovery from optical flow
International Journal of Reconfigurable Computing - Special issue on selected papers from ReConFig 2008
Journal of Intelligent and Robotic Systems
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
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This paper addresses the challenge of supporting real-time vision processing on-board small autonomous vehicles. Local vision gives increased autonomous capability, but it requires substantial computing power that is difficult to provide given the severe constraints of small size and battery-powered operation. We describe a custom FPGA-based circuit board designed to support research in the development of algorithms for image-directed navigation and control. We show that the FPGA approach supports real-time vision algorithms by describing the implementation of an algorithm to construct a three-dimensional (3D) map of the environment surrounding a small mobile robot. We show that FPGAs are well suited for systems that must be flexible and deliver high levels of performance, especially in embedded settings where space and power are significant concerns.