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

现代机器人系统不可避免地成为工业4.0计划的核心，以确保灵活的生产和最佳的资源配置。因此，除了常见的工业固定机器人系统和传统的固定工作站外，自动引导机器人系统、协作和移动操作、广泛的全球和局部传感系统以及可重构的自动化工作站变得越来越重要。然而，尽管在生产线上增加复杂系统带来了新的机会并有助于提高生产的灵活性，但由于多余的作用者资源、更高的危险可能性和昂贵的维护费用等原因，它也导致了额外的成本。如果不完全认识和开发资源的潜力，就不能保证整个系统在这种复杂的生产场景中的最优化。因此，在本提案中，申请人强加了以下主要假设：网络物理混合移动机器人系统与全球和本地传感器系统一起为智能工厂引入创新能力，增加了整个系统的额外冗余，并可通过最优的综合控制来确保弹性、效率和人与机器人的安全交互。在这方面，申请者的目标是应对在未来智能工厂中准备资源所应面临的挑战。具体地说，考虑安装在移动平台上的机器人机械手，因为它们在生产线上引入了新的机会，因为它们具有很大的冗余度，而且不同部件的组合具有复杂的交互作用，从而产生进一步的创新。在拟议的工作计划中，申请者的目标是认识和开发此类系统的冗余潜力，并开发模型将其整合到高级工艺规划中，以实现效率和弹性，同时保证人与机器人的安全交互。到目前为止，这些资源还没有得到充分的研究，以帮助整个过程控制的优化设计。需要解决的不足可分为：(1)混合式移动机器人的模块化全身建模策略；(2)这些机器人的运动控制和规划技术；(3)在工业场景中将这些运动生成技术集成到工艺规划算法中。

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.