Analysis, design and control of collaborative robots for extended reach dexterous assembly

装配是制造复杂产品所需工作的重要组成部分。 由于装配需要高度的灵巧性和灵活性，因此通常仍由人类操作员执行。 然而，人类操作员受到人体工程学约束的限制，例如有限的范围、力、姿势和其他因素。另一种方法是使用自动化。然而，尽管机器人技术最近取得了进步，但今天的自主机器人技术无法满足人类操作员特有的速度和可靠性标准。因此，涉及人类和协作机器人的解决方案-支持人类操作员的努力-在最近的文献中进行了研究。在本研究项目中，建议通过开发一种人工辅助解决方案来扭转这种范式。 在这个概念中，装配机器人设备将被设计为在人类操作员的全局控制下运行。 拟议的辅助设备将直接参与灵巧的装配，从而使任务扩展到超出人类的范围或力的限制。首先，将追求一类有针对性的灵巧的任务，包括集成的被动和/或主动的解决方案和所需的控制算法的装配力学建模。然后，将开发在硬件和控制方面提供增力的手段。两个家庭的机器人概念，然后将进行调查，即一个简单的机械概念，有限的能力，和一个完全主动的解决方案，先进的人力辅助能力。将为这两种解决方案中的每一种建立一个原型。原型将被用来证明所提出的方法在制造业的背景下的有效性。 然后，将采用传感和统计分析技术，制定战略，用于可靠地检测拟议原型的组装任务的完成情况。 这包括适合工业应用的机器学习框架。最后，将开发简单的人机界面，以展示开发的机器人概念的直观编程，从而展示它们在工业应用中的相关性。

Assembly represents a significant portion of the effort required for the manufacturing of complex products. Since assembly requires a high level of dexterity and flexibility, it is still generally performed by human operators. Human operators, however, are limited by ergonomic constraints such as limited reach, forces, posture and other factors. An alternative is the use of automation. However, despite the recent advances in robotics technology, autonomous robotics today cannot meet the standards of speed and reliability that are characteristic of human operators. Therefore, solutions involving humans and collaborative robots - that support the efforts of human operators - have been investigated in the recent literature. In this research project, it is proposed to invert this paradigm by developing a human-assisted solution. In this concept, assembly robotic devices will be designed that function under the global control of human operators. The proposed assistive devices will directly participate in the dexterous assembly, and thus allow tasks to extend beyond the reach or force constraints of humans. First, the modelling of the mechanics of assembly will be pursued for a class of targeted dexterous tasks including the integration of passive and/or active solutions and the control algorithms needed. Then, means of providing force augmentation in hardware and controls will be developed. Two families of robotic concepts will then be investigated, namely a simple mechanical concept with limited capability, and a fully active solution with advanced human-assisted capability. A prototype will be built for each of these two types of solutions. The prototypes will be used to demonstrate the effectiveness of the proposed approach in a context of manufacturing. The development of strategies for the reliable detection of the completion of an assembly task with the proposed prototypes will then be pursued using sensing and statistical analysis techniques. This includes a machine learning framework suitable for an industrial application. Finally, simple Human-Machine interfaces will be developed in order to demonstrate the intuitive programming of the developed concepts of robots and thereby their relevance in industrial applications.**********