DocumentCode :
1950458
Title :
A crash avoidance system based upon the cockroach escape response circuit
Author :
Chen, Chun-Ta ; Quinn, Roger D. ; Ritzmann, Roy E.
Author_Institution :
Mech. & Aerospace Eng., Case Western Reserve Univ., Cleveland, OH, USA
Volume :
3
fYear :
1997
fDate :
20-25 Apr 1997
Firstpage :
2007
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
Keywords :
automobiles; backpropagation; control system synthesis; controllability; mobile robots; motion control; neural net architecture; path planning; robot dynamics; robot kinematics; American cockroach; automobiles; cockroach escape response circuit; crash alarm strategy; crash avoidance system; distributed network; dynamic environment; four-wheeled vehicle; front wheel steering; neural organization; reflexive crash avoidance behaviors; Artificial neural networks; Automobiles; Circuits; Collision avoidance; Computer crashes; Neurons; Real time systems; Vehicle crash testing; Vehicle dynamics; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 1997. Proceedings., 1997 IEEE International Conference on
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3612-7
Type :
conf
DOI :
10.1109/ROBOT.1997.619164
Filename :
619164
Link To Document :
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