Path Planning of a Mobile Robot in Outdoor Terrain
In this study, we discuss the path planning of mobile a robot using an aerial image. Many times mobile robots are to be deputed to go to far off lands on a mission over uneven outdoor terrains. The aerial image available either as satellite images or produced by aerial drones can be used to construct a rough path for the navigation of the mobile robot. First Gaussian Process Bayesian classifier is used to classify the different classes of terrain. Next each class is associated with a cost denoting the cost of traversal of a unit distance in that particular domain. The costs account for the energy costs, risk of accidents, etc. These numerical values corresponding to each location are called as a costmap, and that array of costmap is passed to the A* algorithm which is a graph search algorithm. The A* algorithm gives the optimal path. The final result is shown in the form of the path over the aerial image with different resolutions and samples of the image.
KeywordsRobot motion planning Outdoor robotics A* algorithm Graph search Gaussian process bayesian classifier
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