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

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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.