Abstract:
The application of mobile robots in autonomous navigation has con-tributed to the development of exploration tasks for the recognition of unknown environments. There are different methodologies for obstacles avoidance imple-mented in mobile robots, however, this research introduces a novel approach for a path planning of an Unmanned Ground Vehicle (UGV) using the camera of a drone to get an aerial view that allows to recognize ground features through im-age processing algorithms for detecting obstacles and target them in a determined environment. After aerial recognition a global planner with Rapidly-exploring Random Tree Star (RRT*) algorithm is executed, Dubins curves are the method used in this case for nonholonomic robots. The study also focuses on determining the compute time which is affected by a growing number of iterations in the RRT*, the value of step size between the tree’s nodes and finally the impact of number of obstacles placed in the environment. This project is the initial part of a larger research about a Collaborative Aerial-Ground Robotic System.
