Multi-robot Cooperation for Assembly: Automated Planning and Optimization

In the field of industry 4.0 and smart factories of the future, dynamic teams of robots will play an important role in the manufacturing of custom-tailored products with small lot sizes. Especially the planning for such multi-functional robot cells forms a key challenge, finding appropriate tasks for cooperating robots to perform efficient production. In this paper, we present two approaches for automated planning of assembly programs for multiple robots that separate between domain and automation level. While one uses a decomposition approach with plan-space planning and explicit decomposition rules, the other considers heuristic searching in state space. Both approaches are evaluated with different planning problems in the blocks world domain (i.e., LEGO® DUPLO®). The evaluation shows that both approaches outperform the results achieved with classical planning based on state-space search such as \(A^*\). Furthermore, a concept for post-processing programs to optimize execution time by dependency-based interleaving of robot tasks is introduced that fully integrates into both planning approaches.