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

许多制造作业要求工人在狭小的空间内进行操作，这可能会使他们在非人体工程学姿势下执行繁琐的任务时感到疲劳和受伤。智能机器人助手可以帮助安全和符合人体工程学的方式进入这样的空间，同时允许人类工人保持身体在场并完全控制精细的操作。该项目将调查高度可重新配置的就地协作机器人(ISCR)的使用，这些机器人具有增强的感知和支持自主性，使工人和机器人能够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，很难编程。该项目的ISCR预计将减少工人疲劳和肌肉骨骼损伤，这是美国34%以上的工作日损失的原因，并提高工人的生产率。他们增加的智能也有望通过提供一种人类友好的交互方式，使机器人更容易使用。这项研究在航空航天工业中具有潜在的应用，包括机身和机翼的制造和服务，液压管路或燃料箱和管道的检查和维修，填塞，结构接头的焊接和去毛刺。这项支持受限空间中有效的人-机器人协作的工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，3)同时接触力和导航(SCAN)规划，使机器人能够使用支撑在受限空间进行深部操纵。ISCR允许对几何不确定性、减少的惯性、接触感应和与环境相互作用的可调节作用力的合规性和健壮性。这种新的设计使接触状态检测的实时估计、约束识别的螺旋理论方法和刚度建模的探索成为可能。这项研究还将开发规划器，以在具有不确定性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.