Long robotic arms are useful for many applications such as nuclear plant decommissioning, inspection, and firefighting. A major problem for designing and operating long robotic arms is that even small end effector reaction forces and arm gravity can result in large loads on proximal arm joints because of long moment arms. To solve that problem, previous researches focus on specifically designed long arms with certain compensation mechanisms. However, those specialized arm designs are difficult to be applied to existing long robotic arms and to be customized for different missions. To overcome those two drawbacks, we recently proposed a watch-like thrust-generating modular device, called flying watch, with the following two major advantages. Firstly, flying watch can be attached to different kinds of existing long robotic arms and generate thrusts to enhance arm strength. And we have proposed a thrust planning method for flying watch in our previous work. Secondly, since different flying watch attachment allocations can enhance the same robotic arm in different ways, flying watch attachment allocations can be customized to meet the needs of a specific mission. However, up to now, customizing flying watch attachment allocations to different missions is still based on human experience and there is no clear performance metric and automated design method for flying watch attachment allocation. To facilitate mission-dependent long arm enhancement, in this paper, we first propose a novel performance metric, called thrust drivability, which measures the ability of a flying watch attachment allocation to counteract unexpected end effector reaction forces. Then based on thrust drivability, we propose an automated design method, called Allocation Optimization based on Weighted Situations (AOWS), for generating mission-dependent flying watch attachment allocations counteracting both unexpected and known external forces. Simulations show that AOWS based allocation designs can counteract both known and unexpected external forces much better than human-experience-based allocation designs.

中文翻译：

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向任务相关的长机械臂增强：基于推力可驱动性的飞行手表附件分配设计方法

长机械臂可用于许多应用，例如核电站的退役，检查和消防。设计和操作较长的机械臂的主要问题是，由于臂的力矩较长，即使很小的末端执行器反作用力和臂重力也会在近端臂关节上产生较大的负载。为了解决这个问题，以前的研究集中在专门设计的带有某些补偿机制的长臂上。但是，那些专门的手臂设计很难应用于现有的长型机器人手臂，并且难以针对不同的任务进行定制。为了克服这两个缺点，我们最近提出了一种手表式推力生成模块化设备，称为飞行手表，它具有以下两个主要优点。首先，飞行手表可以连接到现有的各种不同的长机械手臂上，并产生推力以增强手臂强度。并且我们在先前的工作中提出了用于飞行表的推力计划方法。其次，由于不同的飞行手表附件分配可以以不同的方式增强同一个机械臂，因此可以定制飞行手表附件分配以满足特定任务的需求。但是，到目前为止，仍然根据人类经验为不同任务定制飞行手表附件分配，并且尚没有明确的性能指标和自动设计方法来进行飞行手表附件分配。为了促进与任务相关的长臂增强，在本文中，我们首先提出了一种新颖的性能指标，称为推力可驱动性，它衡量飞行手表附件分配抵抗意外的末端执行器反作用力的能力。然后，基于推力可驱动性，我们提出了一种自动设计方法，称为基于加权情况的分配优化（AOWS），用于生成与任务相关的飞行值班表附件分配，以抵消意外和已知外力。仿真表明，基于AOWS的分配设计可以比基于人的经验的分配设计更好地抵消已知和意外的外力。用于生成与任务相关的飞行手表附件分配，以抵消意外的和已知的外力。仿真表明，基于AOWS的分配设计可以比基于人的经验的分配设计更好地抵消已知和意外的外力。用于生成与任务相关的飞行手表附件分配，以抵消意外的和已知的外力。仿真表明，基于AOWS的分配设计可以比基于人的经验的分配设计更好地抵消已知和意外的外力。