The warp computer: Architecture, implementation, and performance
IEEE Transactions on Computers
An architecture independent programming language for low-level vision
Computer Vision, Graphics, and Image Processing
Machine-independent image processing: performance of apply on diverse architectures
Computer Vision, Graphics, and Image Processing
ALVINN: an autonomous land vehicle in a neural network
Advances in neural information processing systems 1
Fido: vision and navigation for a robot rover
Fido: vision and navigation for a robot rover
Computer Vision Algorithms on Reconfigurable Logic Arrays
IEEE Transactions on Parallel and Distributed Systems
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
VHDL description of a synthetizable and reconfigurable real-time stereo vision processor
ISPRA'05 Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation
Vision-based road detection in automotive systems: a real-time expectation-driven approach
Journal of Artificial Intelligence Research
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The authors review the history of the Carnegie-Mellon Warp machine on Navlab, an autonomous land vehicle, and describe three Navlab vision systems implemented on the Warp machine. They then critically evaluate components of Warp in light of this experience. The Warp machine was used to implement stereo vision for obstacle avoidance and color-based road-following systems. The stereo-vision system was FIDO, which is derived from some of the earliest work in vision-guided robot vehicle navigation. Two color-based road following systems were implemented; one adapted conventional vision techniques to the problem of road recognition and the other used a neural network-based technique to learn road following online. Finally, the authors discuss the value of applications integration with machine development, discuss the limitations of the attached processor model, and give recommendations for future systems.