Crash avoidance system based upon the cockroach escape response circuit

Chun Ta Chen, Roger D. Quinn, Roy E. Ritzmann

Research output: Contribution to journalConference articlepeer-review

13 Citations (Scopus)

Abstract

A crash avoidance system for automobiles is developed based upon a distributed network of artificial neurons that mimic the neural organization of the escape system in the American cockroach. The cockroach escape circuit is shown to be an excellent source of inspiration for the development of a collision avoidance system. The crash avoidance system is implemented in an artificial neural network which is trained off-line, but then is shown to produce real-time performance. A collision avoidance scheme which makes use of a crash alarm strategy is developed for training the neural network. A dynamic model of a four-wheeled vehicle with front wheel steering and realistic performance constraints is used to test the crash avoidance system. Simulation results show that the well-trained neural network causes successful, reflexive crash avoidance behaviors in a dynamic environment without a priori information.

Original languageEnglish
Pages (from-to)2007-2012
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume3
Publication statusPublished - 1997 Jan 1
EventProceedings of the 1997 IEEE International Conference on Robotics and Automation, ICRA. Part 3 (of 4) - Albuquerque, NM, USA
Duration: 1997 Apr 201997 Apr 25

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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