Improving Robotic Teleoperation through Human-Robot Interaction and Robotic Autonomy

远程操作的总体目标是为操作员提供态势感知（即，在那里的感觉）的远程环境和方便地交互的能力。核电厂中的遥控操作员执行检查和维护任务，包括复杂的操作。几项研究表明，环境的非结构化性质，任务的复杂性和核工业的保守性导致远程操作员更喜欢控制并随时充分了解多个系统的当前和未来行为，限制了自主远程操作或机器人技术的部署。因此，这些机械系统的操作员同时与多种媒介进行交互，例如各种显示器、机器人遥控系统、信息系统和其他同事。这些交互对操作员施加了压倒性的信息处理水平，导致高认知工作量，这影响了远程操作的性能和安全性。这项博士研究解决了远程操作中的自动化挑战，重点是提高操作员的性能和安全性。它承认在复杂的非结构化环境中操作员控制的偏好，阻碍了自主系统的部署。它建议集成自适应机器人辅助和响应界面，动态响应操作员的心理工作负荷（MWL）的需求，任务的复杂性和结构。为了实现这一目标，将满足以下目标：识别客观的性能和心理工作负荷指标的遥操作。确定使用任务分析的身体和精神的工作负荷的来源。开发的性能和精神和身体的工作负荷在遥操作的评估方法。设计机器人辅助方案的基础上，身体和精神的需求，以指导操作员通过遥操作任务完成。几件文献已经证明了如何触觉指导的基础上，可以部署机器人援助。例如，触觉共享控制和触觉交换控制，操作员和系统分别在控制任务中共享和轮流。这项工作将探讨如何部署这些援助计划，以响应操作员的身体和认知的需求，在结构化的环境中重复和可预测的任务。它将结合联合收割机的一些生理，主观和性能的措施，给一个改进的评估和评价操作员的心理负荷，了解其与遥操作任务的关系。通过这些改进的系统，操作员可以更方便、更快、更准确地执行工作，提高安全性并降低运营成本。

Teleoperation's overall goal is to give the operator situational awareness (i.e., a sense of being there) of the remote environment and the ability to interact conveniently. Operators of telemanipulators in nuclear plants perform inspections and maintenance tasks, including complex manipulations. Several studies reveal that the unstructured nature of the environment, task complexity, and the conservative nature of the nuclear industry cause teleoperators to prefer to be in control and fully aware of the multiple systems' current and future behaviours at all times, limiting the deployment autonomous teleoperation or robotics. As a result, the operators of these mechanical systems interact with several mediums, such as various displays, robotic telemanipulation systems, information systems, and other colleagues, at once. These interactions impose overwhelming levels of information processing on the operator, leading to a high cognitive workload, which impacts performance and safety in teleoperation.This PhD research addresses the automation challenge in teleoperation, focusing on enhancing operator performance and safety. It acknowledges the preference for operator control in complex, unstructured environments, hindering the deployment of autonomous systems. It proposes integrating adaptive robotic assistance and responsive interfaces that dynamically respond to an operator's mental workload (MWL) demands, task complexity and structure. The following objectives will be met to achieve this aim:To identify the objective performance and mental workload metrics for teleoperation.To determine the sources of physical and mental workload using task analysis.To develop methods for assessment of performance and mental and physical workloads in teleoperation.To design robotic assistance schemes based on physical and mental demands to guide operators through teleoperation task completions.Several pieces of literature have demonstrated how haptic guidance based on the sense of touch can be deployed for robotic assistance. For example, haptic shared control and haptic traded control, which the operators and the system share and take turns in the control task, respectively. This work will explore how these assistance schemes could be deployed to respond to an operator's physical and cognitive demands within structured environments for repetitive and predictable tasks. It will combine some physiological, subjective and performance measures to give an improved assessment and evaluation of the operator's mental workload to understand its relationships with teleoperation tasks. With these improved systems, operators can perform their work more conveniently, faster, and accurately, increasing safety and reducing operating costs.