Integrated Simulation Software for Outdoor Robots Planning and Coordination

This paper involves the development of optimization software and its associated simulator to compute optimum paths to move a group of mobile robots to a given number of targets in a known environment. Genetic algorithms and the Virtual Reality Modeling Language “vrml” are used to design the software and the simulator respectively. It is assumed that the robots are located arbitrary at known starting positions and need to be moved to target positions in a known multi-obstacle three-dimensional environment. The factors considered for finding optimum paths for the group of mobile robots are the size and location of obstacles in the environment and the elevations of the environment. The developed software was tested on an aerial picture taken by a satellite imaging device for an outdoor environment. The size of obstacles, elevations present in the environment and starting positions of the robots and target position are all identified on the digital image in a form of grid map. The genetic algorithm takes information about the environment from the grid map, the results of processed pictures, and searches for optimum paths to move a group of mobile robots to specified targets. It is found that genetic algorithms converge and give better solutions to path planning in an environment where results are difficult to obtain.