Task assignment and motion planning in the presence of obstacles and prioritized targets

The integrated task assignment and motion planing problem of assigning prioritized targets in an obstacles' environment to a homogeneous team of unmanned aerial or ground vehicles is considered. In the problem of interest the targets are characterized by a time varying level of importance and priority, and the vehicles have a minimum turn radius constraint. In order to generate feasible vehicles' trajectories, the obstacles scattered in the environment are taken into account and the vehicles are modeled as either a Dubins or a Reed-Shepp vehicles. The time varying priority issue is addressed by incorporating the vehicles' feasible path length which represents the vehicles' response time and the targets' properties as part of the problem formulation. The investigated (integrated) problem is posed in the form of a decision tree and two algorithms are proposed. An exhaustive search algorithm which improves over run time and provides the best solution encoded in the decision tree, and a greedy algorithm that provides a quick feasible solution. Using sample runs, the performance of the algorithms is compared and evaluated, and the problem parameters are investigated.