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Teleoperation enables controlling complex robot systems remotely, providing the ability to impart human expertise from a distance. However, these interfaces can be complicated to use as it is difficult to contextualize information about robot motion in the workspace from the limited camera feedback. Thus, it is required to study the best manner in which assistance can be provided to the operator that reduces interface complexity and effort required for teleoperation. Some techniques that provide assistance to the operator while freeform teleoperating include: (1) perception augmentation, like augmented reality visual cues and additional camera angles, increasing the information available to the operator; (2) action augmentation, like assistive autonomy and control augmentation, optimized to reduce the effort required by the operator while teleoperating. In this article, we investigate: (1) which aspects of dexterous telemanipulation require assistance; (2) the impact of perception and action augmentation in improving teleoperation performance; and (3) what factors impact the usage of assistance and how to tailor these interfaces based on the operators’ needs and characteristics. The findings from this user study and resulting post-study surveys will help identify task-based and user-preferred perception and augmentation features for teleoperation assistance.
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Designing Interface Aids to Assist Collaborative Robot Operators in Attention Management
As collaborative robots become increasingly widespread in manufacturing settings, there is a greater need for tools and interfaces to support operators who integrate, supervise, and troubleshoot these systems. In this paper, we present an application of the Robot Attention Demand (RAD) metric for use in the design of user interfaces to support operators in collaborative manufacturing scenarios. Building on prior work that introduced RAD, we designed and implemented prototype timeline and countdown-timer interfaces to be used within a collaborative assembly-inspection task where an operator is also responsible for a separate sorting task. We performed a user evaluation to investigate the effects of displaying predictive RAD information on operator performance and perceptions of the task. Our results show lower perceived task load and increased usability scores compared to baseline condition without an interface. These findings suggest that predictive RAD should be used by designers and engineers developing operator interfaces for collaborative robot applications in manufacturing.
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- PAR ID:
- 10286325
- Date Published:
- Journal Name:
- IEEE International Conference on Robot and Human Interactive Communication
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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