Cooperative Trajectory Planning for Automated Farming

Many agricultural tasks, such as harvesting, are labor intensive. With the interests in autonomous farming, a method to rapidly generate trajectories for agricultural robots satisfying different realistic constraints becomes necessary. A hierarchical cooperative planning method is studied in this paper for a group of agricultural robots with a low computational cost. Two parts are involved in the method: once a reconfiguration event is confirmed, all the possible formation configurations will be evaluated and ranked according to their feasibility and performance index; a local pursuit strategy based cooperative trajectory planning algorithm is designed to generate optimal cooperative trajectories for robots to achieve and maintain their desired formation. To help reduce the computation cost associated with the cooperative planning algorithm, early termination conditions are proposed. The capabilities of the proposed cooperative planning algorithm are demonstrated in a simple citrus harvesting problem.