Type of Document Master's Thesis Author Putney, Joseph Satoru Author's Email Address firstname.lastname@example.org URN etd-05252006-134900 Title Reactive Navigation of an Autonomous Ground Vehicle Using Dynamic Expanding Zones Degree Master of Science Department Mechanical Engineering Advisory Committee
Advisor Name Title Reinholtz, Charles F. Committee Chair Hong, Dennis W. Committee Member Wicks, Alfred L. Committee Member Keywords
- Dynamic Expanding Zones
- Fuzzy Logic
- Unmanned Ground Vehicle
- Mobile Robots
- Autonomous Vehicles
- Reactive Navigation
Date of Defense 2006-05-11 Availability unrestricted AbstractAutonomous navigation of mobile robots through unstructured terrain presents
many challenges. The task becomes even more difficult with increasing obstacle density,
at higher speeds, and when a priori knowledge of the terrain is not available. Reactive
navigation schemas are often dismissed as overly simplistic or considered to be inferior
to deliberative approaches for off-road navigation. The Potential Field algorithm has
been a popular reactive approach for low speed, highly maneuverable mobile robots.
However, as vehicle speeds increase, Potential Fields becomes less effective at avoiding
The traditional shortcomings of the Potential Field approach can be largely
overcome by using dynamically expanding perception zones to help track objects of
immediate interest. This newly developed technique is hereafter referred to as the
Dynamic Expanding Zones (DEZ) algorithm. In this approach, the Potential Field
algorithm is used for waypoint navigation and the DEZ algorithm is used for obstacle
avoidance. This combination of methods facilitates high-speed navigation in obstaclerich
environments at a fraction of the computational cost and complexity of deliberative
The DEZ reactive navigation algorithm is believed to represent a fundamental
contribution to the body of knowledge in the area of high-speed reactive navigation.
This method was implemented on the Virginia Tech DARPA Grand Challenge vehicles.
The results of this implementation are presented as a case study to demonstrate the
efficacy of the newly developed DEZ approach.
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