Receding-horizon RRT-Infotaxis for autonomous source search in urban environments

In emergency situations such as hazardous gas leak, search and estimation for identifying source information, known as source term estimation (STE), in a timely and accurate manner is of significant importance. In real world situations, obstacles such as buildings or barriers not only block the path for search but also interfere the flow of the gas source. For autonomous source search and estimation using a mobile sensor in such obstacle-rich environments, this paper proposes an information-theoretic STE approach by combining a widely-used Infotaxis with the rapidly-exploring random trees (RRT). In particular, the proposed strategy utilizes the receding-horizon RRT concept with a newly designed utility function for determining the next maneuver of a mobile agent to get the best information of the source while avoiding obstacles in urban environments. Numerical simulations in various environments show the superior performance of the proposed approach compared with the original Infotaxis method.