Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.
We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.
Wright
Cameron H G
CH
University of Wyoming, Laramie, Wyoming, USA. chg@uwyo.edu
Barrett
Steven F
SF
Pack
Daniel J
DJ
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D040761:Biomimetic Materials; D016000:Cluster Analysis; D003205:Computing Methodologies; D004867:Equipment Design / Q000379:methods; D019544:Equipment Failure Analysis; D006793:Houseflies; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D009068:Movement; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*; D017956:Photoreceptor Cells, Invertebrate / Q000502:physiology*; D012371:Robotics / Q000295:instrumentation / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014159:Transducers