Evolution-Based Deliberative Planning for Cooperating Unmanned Ground Vehicles in a Dynamic Environment

Talib Hussain, David Montana, and Gordon Vidaver

Abstract. Many challenges remain in the development of tactical planning systems that will enable automated, cooperative replanning of routes and mission assignments for multiple unmanned ground vehicles (UGVs) under changing environmental and tactical conditions. We have developed such a planning system that uses an evolutionary algorithm to assign waypoints and mission goals to multiple UGVs so that they jointly achieve a set of mission goals. Our evolutionary system applies domain-specific genetic operators, termed tactical advocates because they capture specific tactical behaviors, to make targeted improvements to plans. The plans are evaluated using a set of tactical critics that together comprise a multiobjective fitness function. Each critic evaluates a plan against criteria such as avoiding an enemy or meeting mission goals. Experimental results show that this approach produces highquality plans with the potential for real-time dynamic replanning.

LNCS 3103, p. 1017 ff.

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