This paper describes one aspect of our approach in developing an intelligent off-road autonomous vehicle, the Intelligent Off-road Navigator (ION), as team Desert Buckeyes from the Ohio State University for the DARPA Grand Challenge 2005. The real-time navigation is one of the critical components in an autonomous ground vehicle system. In this paper, we focus on the navigation module, whose main responsibility is to generate smooth and obstacle-free local paths with appropriate speed setpoints. For the smooth path generation, we introduce a polynomial interpolation method. To generate obstacle-free paths, a steering controller utilizing a fuzzy obstacle avoidance algorithm is presented. A speed fuzzy controller is introduced to generate the speed setpoints. These two fuzzy controllers collaborate with each other to guide our vehicle ION to the goal safely. The obstacle avoidance algorithm proposed in this paper was also tested in simulations and on small robots successfully. Other issues related to the navigation module are discussed in the paper as well, such as the vehicle’s system structure and its finite state machine. As a result, ION achieved great performance in the National Qualification Event (NQE), covered about 30miles in the Nevada Desert with complete autonomous operations, and finished 10th in the Grand Challenge 2005.
Intelligent Off-Road Navigation Algorithms and Strategies of Team Desert Buckeyes in the DARPA Grand Challenge ’05
2007-01-01
21 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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