In this paper, we present the Diver Interest via Pointing (DIP) algorithm, a highly modular method for conveying a diver's area of interest to an autonomous underwater vehicle (AUV) using pointing gestures for underwater humanrobot collaborative tasks. DIP uses a single monocular camera and exploits human body pose, even with complete dive gear, to extract underwater human pointing gesture poses and their directions. By extracting 2D scene geometry based on the human body pose and density of salient feature points along the direction of pointing, using a low-level feature detector, the DIP algorithm is able to locate objects of interest as indicated by the diver. DIP makes it possible for scuba divers and swimmers to use directional cues, through pointing, to an AUV for inspection, surveillance, manipulation, and navigation. We examine the elements that make up our method, provide quantitative and qualitative evaluation, and demonstrate AUV actuation based on diver pointing gestures in closed-water human-robot collaborative experiments. Our evaluations demonstrate the high efficacy of the DIP algorithm in correctly identifying the direction of a pointing gesture and locating an object within that region of interest. We also show that the findings of the algorithm qualitatively conform with human assessment of pointing gestures, directions, and targets.
|Original language||English (US)|
|Title of host publication||Proceedings - ICRA 2023|
|Subtitle of host publication||IEEE International Conference on Robotics and Automation|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||8|
|State||Published - 2023|
|Event||2023 IEEE International Conference on Robotics and Automation, ICRA 2023 - London, United Kingdom|
Duration: May 29 2023 → Jun 2 2023
|Name||Proceedings - IEEE International Conference on Robotics and Automation|
|Conference||2023 IEEE International Conference on Robotics and Automation, ICRA 2023|
|Period||5/29/23 → 6/2/23|
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