Title :
All-weather and all-terrain intelligent vehicle for law enforcement applications
Author_Institution :
Cracow Univ. of Technol., Krakow, Poland
Abstract :
The author selected neuro-fuzzy reasoning based motion control that is propulsion, dispulsion, suspension and conversion control algorithms to the mechatronically controlled intelligent vehicle. Fuzzy logic was chosen because of the following characteristics. It is easier to implement driver skills using neuro-fuzzy reasoning based motion control than using conventional motion control algorithms. It filters even the uncertainty of the precision of the sensors. Therefore, the intelligent vehicle may move as smoothly as a well-skilled or experienced human being along straight and curved routes on the hostile location or battlefield. Motion control for an intelligent vehicle requires many of the same elements that the military command, control communication and intelligence (C3I) systems use. The all-weather and all-terrain intelligent vehicle will have two types of moving mode, IR vision-camera mode and US sonar mode, originating from the differing methods used to detect the intelligent vehicle position.
Keywords :
fuzzy control; fuzzy neural nets; infrared imaging; intelligent control; mechatronics; neurocontrollers; position measurement; ultrasonic applications; vehicles; IR vision-camera mode; US sonar mode; all-weather all-terrain intelligent vehicle; conversion control; dispulsion; fuzzy logic; law enforcement applications; mechatronically controlled intelligent vehicle; motion control; neuro-fuzzy reasoning; position detection; propulsion; suspension; Filters; Fuzzy logic; Intelligent sensors; Intelligent vehicles; Law enforcement; Motion control; Propulsion; Sensor phenomena and characterization; Sonar detection; Uncertainty;
Conference_Titel :
Intelligent Vehicles '94 Symposium, Proceedings of the
Print_ISBN :
0-7803-2135-9
DOI :
10.1109/IVS.1994.639570