Abstract
Teleoperation enables complex robot platforms to perform tasks beyond the scope of the current state-of-the-art robot autonomy by imparting human intelligence and critical thinking to these operations. For seamless control of robot platforms, it is essential to facilitate optimal situational awareness of the workspace for the operator through active telepresence cameras. However, the control of these active telepresence cameras adds an additional degree of complexity to the task of teleoperation. In this paper we present our results from the user study that investigates: (1) how the teleoperator learns or adapts to performing the tasks via active cameras modeled after camera placements on the TRINA humanoid robot; (2) the perception-action coupling operators implement to control active telepresence cameras, and (3) the camera preferences for performing the tasks. These findings from the human motion analysis and post-study survey will help us determine desired design features for robot teleoperation interfaces and assistive autonomy.
| Original language | English (US) |
|---|---|
| Article number | 3571599 |
| Journal | ACM Transactions on Human-Robot Interaction |
| Volume | 12 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 27 2023 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Artificial Intelligence
Keywords
- active telepresence
- Additional Key Words and PhrasesPerception-action coupling
- robot teleoperation
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