Redundancy for resilience in smart factories of the future through hybrid mobile robotic systems

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Modern robotic systems are inevitably core of the industry 4.0 initiative to guarantee flexible production with optimal resource allocation. Thus, beside common industrial stationary robotic systems and traditional fixed workstations, automated guided robotic systems, collaborative and mobile manipulation, extensive global and local sensoric systems and reconfigurable automated workstations gain increasing significance. Nevertheless, while adding complex systems to the production lines introduces new opportunities and contributes to the flexibility of the production, it also results in additional costs due to redundant actoric resources, higher possibility of hazard, expensive maintenance, etc. Without complete recognition and exploitation of the potentials of the resources, the optimality of the whole system in such complex production scenarios cannot be guaranteed. Therefore, in this proposal, the applicants impose the following main hypothesis: Cyber physical hybrid mobile robotic systems together with global and local sensor systems introduce innovative capabilities to the smart factories which add additional redundancies to the whole system and can be exploited to guarantee resilience, efficiency and safe human-robot interaction through optimal comprehensive control. In this regard, the applicants aim to address the challenges that should be met to prepare the resources in smart factories of the future. Specifically, robotic manipulators mounted on mobile platforms are considered since they introduce new opportunities in production lines due to their large degrees of redundancy and composition of different components with complex interaction that yields further innovation. In the proposed work program, the applicants aim to recognize and exploit the redundancy potentials of such systems and develop models to integrate them in high-level process planning to achieve efficiency and resilience while guaranteeing safe human-robot interaction. So far, these resources have not been fully studied to contribute to the optimal design of the overall process control. The deficits that still need to be addressed can be categorized into: (1) modular whole-body modeling strategies for hybrid mobile robots, (2) motion control and planning techniques for these robots and (3) the integration of such motion generation techniques into process planning algorithms in industrial scenarios.