Job Allocation And Scheduling In Multi Robotic Tasks Considering Collision Free Operation

This paper presents a method of job allocation and scheduling that determines optimal job allocation and the shortest paths for robots having collision regions. The problem described in this paper is an application of a classical flexible job-shop scheduling problem with shared resources. A genetic algorithm and a TABU search are used for the job allocation and scheduling procedures. Overlapping activities in a collision region can result in robot collisions. This should be a hard constraint in which a non-overlapping condition is guazanteed. To achieve this, the sequencing in a collision region should be determined. Job assignrnents, ordering in non-collision regions of each robot, and priorities in regions shazed between various robots are encoded using a genetic representation in which the objective is to minimize the job completion time. As the seazch space is extremely large, a genetic algorithm is used for global searches and TABU is used for local searches. The most viable solution is obta...