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

许多制造作业要求工人在密闭空间内进行操作，使他们可能因以非人体工程学的姿势执行繁琐的任务而疲劳和受伤。智能机器人助手可以安全、符合人体工程学的方式进入这些空间，同时允许人类工作人员留在现场，并完全控制精细的操作。该项目将研究高度可重构的原位协作机器人（ISCRs）的使用，该机器人具有增强的感知和支持自主性，需要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。传统的机器人不能作为iscr使用，因为它们体积庞大，用途特殊，而且难以编程。该项目的iscr有望减少工人的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，并提高工人的生产力。通过提供对人类友好的互动方式，它们增加的智能也有望使机器人更容易使用。这项研究在航空航天工业中有潜在的应用，包括机身和机翼的制造和维修，液压管线或油箱和管道的检查和修理，结构接头的填缝，焊接和去毛刺。这项工作支持在密闭空间中有效的人机协作，主要有三个技术贡献：1)iscr的设计和控制策略，2)接触检测和位置估计，以及3)同步接触力和导航（SCAN）规划，以便机器人可以使用支撑装置深入密闭空间。iscr允许几何不确定性的顺应性和鲁棒性，减少惯性，接触传感和与环境相互作用的调节力。这种新设计可以探索接触状态检测的实时估计，约束识别的螺杆理论方法和刚度建模。该研究还将制定计划，在不确定的半结构化环境中实现扫描，并将使用有意接触，使机器人能够深入受限空间。

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.