Mobile robot navigation using qualitative reasoning

Conference · Fri Jan 01 04:00:00 EST 1993

OSTI ID:7068043

Pin, F G; Watanabe, Yutaka

Vehicle control in a priori unknown, unpredictable, and dynamic environments requires many calculational and reasoning schemes to operate on the basis of very imprecise. incomplete, or unreliable data. Forsuch systems, in which all the uncertainties can not be engineered away, approximate reasoning may provide an alternative to the complexity and computational requirements of conventional uncertainty analysis and propagation techniques. Two types of computer boards including custom-designed VLSI chips have been developed to add a fuzzy inferencing capability to real-time control systems. The use of these boards and anapproach using superposition of elemental sensor-based behaviors for the development of qualitative reasoning schemes emulating human-like navigation are first discussed. We then describe how the human-like navigation schemes were implemented on a test-bed platform to investigate two control modes for driving a car in a priori unknown environments on the basis of sparse and imprecise sensor data. In the first mode, the car navigates fully autonomously, while in the second mode, the system acts as a driver's aid providing the driver with linguistic (fuzzy) commands to turn left or right and speed up or slow down depending on the obstacles perceived by the sensors. Experiments with both nodes of control are described in which the system uses only three acoustic range (sonar) sensor channels to perceive the environment. Simulationresults as well as indoors and outdoors experiments are presented and discussed to illustrate the feasibility and robustness of autonomous navigation and/or safety enhancing driver's aid using the new fuzzy inferencing hardware system and methodologies.

• Research Organization: Oak Ridge National Lab., TN (United States)
• Sponsoring Organization: DOE; USDOE, Washington, DC (United States)
• DOE Contract Number: AC05-84OR21400
• OSTI ID: 7068043
• Report Number(s): CONF-930403-26; ON: DE93008277
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
420200* -- Engineering-- Facilities
Equipment
& Techniques
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
ARTIFICIAL INTELLIGENCE
COMPUTERIZED CONTROL SYSTEMS
CONTROL SYSTEMS
FUZZY LOGIC
MATHEMATICAL LOGIC
NAVIGATION
ON-LINE CONTROL SYSTEMS
ON-LINE SYSTEMS
REAL TIME SYSTEMS
ROBOTS