Abstract
This paper gives an overview of an analog implementation for neural processing of compound eye sensors in robotic control. The author has successfully produced several working robotic devices guided by compound eye vision. Vision processing and control feedback are accomplished using both electronic analog neural nets and real-time, hardware-in-the-loop software neurons. To date, the author has integrated compound eye controllers with great success on four robotic systems. These systems exhibit robust motion tracking and detection of light sources and patterns. This paper describes an all-analog, 8-ommatidia pendulum ping-pong player and its neural implementation. The concepts given in this paper are fairly general and can be applied to any compound eye sensing system. The author's main finding is the amazing robotic behavior possible using incredibly simple neural control strategies. >
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
