NRI: INT: MANUFACTURING USA: COLLAB: In-Situ Collaborative Robotics in Confined Spaces

许多制造操作要求工人在有限的空间中执行操作，使他们可能因以非人体工程学姿势执行繁琐的任务而感到疲劳和受伤。智能机器人助手可以促进安全和符合人体工程学的进入这些空间，同时允许人类工作人员保持身体存在并完全控制精细操作。该项目将研究高度可重构的原位协作机器人（ISCR）的使用，这些机器人具有增强的感知和支持自主性，允许工人和机器人安全地共享公共空间并通过物理交互进行协作。传统的机器人不能用作ISCR，因为它们体积庞大，用途特殊，难以编程。该项目的ISCR预计将减少工人疲劳和肌肉骨骼损伤，这是造成美国34%以上工作日损失的原因，并提高工人生产力。他们增加的智能也有望通过提供人性化的交互方式使机器人更容易使用。该研究在航空航天工业中具有潜在的应用前景，包括机身和机翼的制造和维修，液压管路或油箱和管道的检查和维修，填缝，结构接头的焊接和去毛刺。这项支持在有限空间中有效人机协作的工作做出了三个主要的技术贡献：1）ISCR的设计和控制策略，2）接触检测和位置估计，以及3）同时接触力和导航（SCAN）规划，以便机器人可以使用支撑深入到有限空间中。ISCR允许对几何不确定性、减小的惯性、接触感测和与环境相互作用的调节力的顺应性和鲁棒性。这种新的设计，使接触状态检测的实时估计，螺旋理论的约束识别方法，和刚度建模的探索。该研究还将开发规划人员，以在具有不确定性的半结构化环境中实现SCAN，并将使用有意接触，使机器人能够深入到密闭空间。

Many manufacturing operations require workers to perform operations in confined spaces, subjecting them to possible fatigue and injury from performing tedious tasks in non-ergonomic postures. Intelligent robotic assistants can facilitate safe and ergonomic reach into such spaces, while allowing human workers to remain physically present and in full control over delicate operations. The project will investigate the use of highly reconfigurable, in-situ, collaborative robots (ISCRs) with the enhanced perception and support-autonomy needed to allow a worker and a robot to safely share a common space and collaborate through physical interaction. Conventional robots cannot be used as ISCRs because they are bulky, special-purpose and difficult to program. This project's ISCRs are expected to reduce worker fatigue and musculoskeletal injuries, which are responsible for more than 34 percent of lost work days in the United States, and increase worker productivity. Their added intelligence is also expected to make the robots easier to use, by offering a human-friendly means of interaction. The research has potential applications in the aerospace industry, including the manufacture and service of the fuselage and wings, inspection and repair of hydraulic lines or fuel tanks and pipes, caulking, welding of structural joints and deburring.This work to support effective human-robot collaboration in confined spaces makes three main technical contributions: 1) design and control strategies for ISCRs, 2) contact detection and location estimation and 3) simultaneous contact-force and navigation (SCAN) planning, so that a robot can use bracing to maneuver deep into a confined space. The ISCRs allow compliance and robustness to geometric uncertainty, reduced inertia, contact sensing and regulated force of interaction with the environment. This new design enables the exploration of real-time estimation for contact state detection, a screw-theoretic approach for constraint identification, and stiffness modeling. The research will also develop planners to achieve SCAN within a semi-structured environment with uncertainty and will use intentional contact to allow enable the robot to reach deep into confined spaces.