CHS: Small: Understanding Environment Perception and Task Performance in Human-in-the-Loop Tele-robotic Systems (HiLTS)

人体具有高度灵巧的操作能力。这种灵活性是经过多年的发展和完善的，基于在许多不同的环境中，在不同类型的约束条件下，反复练习执行操作任务的触摸或触觉反馈。然而，在某些情况下，对环境或身体的限制阻止了直接操作。对于这些情况，如微创手术机器人、拆弹机器人和假肢，可以通过使用协作机器人来提供操作。这种机器人或触觉设备，被称为人在环远程机器人系统（HiLTS），提供急需的触觉反馈，就像自然四肢直接进行操作一样。HiLTS旨在扩展并在某些情况下提高人类操作员在虚拟和远程环境中的灵巧能力。然而，人类用户从触觉设备接收到的信息可能会被所使用的硬件和软件机制所扭曲。现有的研究主要集中于在人类探索远程环境时提供触觉设备的稳定性，而这种对稳定性的关注通常会导致与远程环境物理特性相关的信息（如刚度）的权衡。因此，该项目旨在了解稳定性和刚度之间的权衡如何影响用户对远程环境的理解以及在环境中执行灵巧任务的能力。这些知识可用于改进协作机器人系统在许多不同应用环境中的功能，包括医疗保健、国防和制造业。本课题旨在探讨在遥控机器人系统中通过触觉反馈提供灵巧操作的研究问题。然而，灵巧的操作取决于远程机器人如何很好地融入操作员的感觉运动控制方案。经验证据表明，触觉反馈可以提高灵巧性。不幸的是，添加触觉反馈，特别是动觉反馈会在远程机器人的领导者和追随者之间引入动态，从而影响稳定性和设备性能。协同研究的重点是使这些设备的动态对操作员透明，同时保持稳定性。然而，真正的透明度只是理论上的理想，而不是可以实现的目标。因此，项目团队将通过建立对远程机器人闭环领导者/追随者动态对远程环境感知和需要该环境知识的任务表现的影响的经验理解，来探索“降低透明度”的影响。利用具有刚性机械传动、动态机械传动和动态机电传动的广义遥控机器人试验台，研究团队将(1)独立和集体地研究环境刚度和阻尼的触觉感知，使用具有刚性和动态领导/跟随传动的机械遥控机器人；(2)研究在两种需要环境动力学知识的功能任务中的表现，分别使用刚性机械遥操作器和具有闭环领导/跟随动力学的机电遥操作器；(3)研究具有对称和非对称领导/跟随动力学的双手机械遥操作器和机电遥操作器的触觉感知和功能任务表现。除了触觉反馈外，研究还将考虑视觉反馈的效用。总的来说，这项研究将使远程机器人更接近于其操作员的体现，并将提高人机协作能力，这将在许多不同的行业，包括医疗保健、国防和制造业中受益。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The human body is highly capable of dexterous manipulation. This dexterity is developed and refined over many years based on touch or tactile feedback from repeated practice performing manipulation tasks in many different environments with varying types of constraints. There are situations, however, where constraints on the environment or body prevent direct manipulation. For these situations, such as minimally invasive surgical robots, bomb disposal robots, and prosthetic limbs, manipulation can be provided through the use of collaborative robots. Such robots or haptic devices, called human-in-the-loop telerobotic systems (HiLTS), provide the much-needed tactile feedback as with the natural limbs working on the manipulations directly. HiLTS are designed to extend and, in some circumstances, improve the dexterous capabilities of the human operator in virtual and remote environments. However, the information that the human user receives from the haptic devices can be distorted by the hardware and software mechanisms used. Existing research focus mostly on providing stability of the haptic devices as humans explore a remote environment and such a focus on stability can typically lead to a trade-off in the information (such as stiffness) pertaining to the physical properties of the remote environment. This project, therefore, seeks to understand how the trade-off between stability and stiffness affect the user's understanding of a remote environment and the ability to perform dexterous tasks in the environment. This knowledge can then be used to improve the functionality of collaborative robotic systems used in many different application contexts, including healthcare, defense, and manufacturing. This project addresses the research issues in providing dexterous manipulations through haptic feedback in telerobotic systems. Dexterous manipulation, however, depends on how well the telerobot is incorporated into the operator's sensorimotor control scheme. Empirical evidence suggests that haptic feedback can lead to improved dexterity. Unfortunately, the addition of haptic feedback, in particular, kinesthetic feedback can introduce dynamics between the leader and follower of the telerobot that can affect both stability and device performance. Concerted research efforts have focused on making these device dynamics transparent to the operator while preserving stability. True transparency, however, represents a theoretical ideal rather than an attainable goal. Therefore, the project team will explore the effect of "reduced transparency" by establishing an empirical understanding of the effect of a telerobot's closed-loop leader/follower dynamics on the perception of a remote environment and performance in tasks requiring knowledge of that environment. Utilizing a generalized telerobotic testbed that features a rigid mechanical, dynamic mechanical, and dynamic electromechanical transmission, the research team will (1) independently and collectively investigate haptic perception of environment stiffness and damping using a mechanical teleoperator with rigid and dynamic leader/follower transmissions, (2) investigate performance in two functional tasks requiring knowledge of environment dynamics using a rigid mechanical teleoperator and an electromechanical teleoperator with closed-loop leader/follower dynamics, and (3) investigate haptic perception and functional task performance with bimanual mechanical and electromechanical teleoperators that have symmetric and asymmetric leader/follower dynamics. Investigations will also consider the utility of visual feedback in addition to haptic sensory feedback. Overall, this research will lead to telerobots that come closer to being embodied by their operators and will lead to improved human-robot collaborative capabilities in HiLTS that will have benefits in many different industries including healthcare, defense, and manufacturing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.