The Mars Surveyor Challenge was introduced by MathWorks as a way to challenge the community of algorithm developers by asking them to come up with a solution to explore a set of given maps using five vehicles, called rovers. The challenge at hand is to find an optimal strategy using MATLAB to explore as much of a map as possible in a limited number of instructions, or 'moves'. This strategy can be used in designing search algorithms for UAVs or other surveillance vehicles in order to perform searches more efficiently. Multiple types of algorithms were studied in order to find their effect on the solution through the Research Experience for Undergraduate Students at the University of Cincinnati. The goal of this project was to develop algorithms that scale well for larger maps and more rovers than those specified for use in the original competition. In particular, this paper explores the use of a rule based algorithm which combines the concepts of stigmergy and receding horizon algorithms to solve the problem. Simulation results show that the algorithm discussed in this document is highly competitive compared to the competition winners and scales to larger maps and number of vehicles maintaining the same level of performance as observed with the original competition conditions.
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