(Georgia Institute of Technology, 2005-12)
Howard, Ayanna M.; Seraji, Homayoun; Werger, Barry
This paper presents a hierarchical strategy for field mobile robots that incorporates path planning at different ranges. At the top layer is a global path planner that utilizes gross terrain characteristics, such as hills and valleys, to determine globally safe paths through the rough terrain. This information is then passed via waypoints to a regional layer that plans appropriate navigation paths using regional terrain characteristics. The global and regional path planners share the same map information, but at different ranges. The motion recommendations from the regional layer are then combined with those of the reactive navigation layer to provide reactive control for the mobile robot. Details of the global and regional path planners are discussed, and simulation and experimental results are presented.
(Georgia Institute of Technology, 2005-10)
Howard, Ayanna M.; Werger, Barry; Seraji, Homayoun
In this paper, we present an approach to transfer human expertise for learning off-road navigation behavior to an autonomous mobile robot. The methodology uses the concept of humanized intelligence to combine principal component analysis and neural network learning to embed human driving expertise onto mobile robots. The algorithms are tested in the field using a commercial Pioneer 2AT robot to demonstrate autonomous traversal over rough natural terrain.
(Georgia Institute of Technology, 2003-09)
Howard, Ayanna M.; Werger, Barry; Seraji, Homayoun
This paper presents a new method for integrating terrain maps into a reactive navigation strategy of field mobile robots operating on rough terrain. The method incorporates the Regional Traversability Map, a fuzzy map representation of traversal difficulty of the regional terrain, into the navigation logic. A map-based regional navigation behavior provides speed and direction recommendations based on the current status of the robot. In addition, recommendations from two sensor-based reactive behaviors, local avoid-obstacle and regional traverse-terrain, are fused with the map-based regional behavior to construct a comprehensive navigation system. The algorithms are tested both in graphical simulations and in the field using a commercial Pioneer 2AT robot to demonstrate traversal over rough natural terrain.