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

协作机器人大范围灵巧装配分析、设计与控制

• 批准号: 493480-2015
• 负责人: Gosselin, Clement
• 金额: $ 8.04万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=652222
• 关键词: Analysis; design; control; collaborative; robots

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.**********

组装代表了制造复杂产品所需的很大一部分。 由于组装需要高水平的灵活性和灵活性，因此它通常由人类操作员执行。 但是，人类操作员受到人体工程学约束的限制，例如覆盖范围，力量，姿势和其他因素。另一种方法是使用自动化。但是，尽管机器人技术最近取得了进步，但如今的自动机器人技术无法符合人类运营商特征的速度和可靠性标准。因此，最近的文献研究了涉及人类和协作机器人的解决方案（支持人类运营商的努力）。在该研究项目中，建议通过开发人类辅助解决方案来颠倒这种范式。 在这个概念中，将在人类操作员的全球控制下设计组装机器人设备。 拟议的辅助设备将直接参与灵巧的组装，从而使任务可以超越人类的覆盖范围或力量限制。首先，将针对一类有针对性的灵巧任务进行组装的建模，包括被动和/或活动解决方案的集成以及所需的控制算法。然后，将开发在硬件和控制措施中提供力量增强的方法。然后将研究两个机器人概念的家族，即具有有限能力的简单机械概念，以及具有先进的人为辅助能力的完全活跃的解决方案。将为这两种类型的解决方案中的每一种制造一个原型。原型将用于在制造业中证明拟议方法的有效性。 然后将使用拟议的原型来开发可靠检测组装任务完成的策略，然后使用传感和统计分析技术来实现。 这包括适用于工业应用的机器学习框架。最后，将开发简单的人机界面，以证明已发达的机器人概念的直观编程，从而在工业应用中相关。****************************