Abstract
Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. An algorithm has been developed for robots which explore the environment to measure the physical properties (temperature in this paper). While the robot is moving, it measures the temperature and registers the value in the corresponding grid cell. The robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, simple gradient following is used. Robust estimation of the gradient using perturbation/correlation is described. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn't have to visit all the grid cells in the environment still providing fast and efficient sensing. Once the robot visited most of the local maximum/minimum, then the gradients at the remaining cells are close to zero. Then, the robot simply follows the Voronoi edges to complete the exploration. The extended algorithm to coordinate multiple robots is shown with simulation results
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