4.6 Article

Diver-Robot Communication Glove Using Sensor-Based Gesture Recognition

Journal

IEEE JOURNAL OF OCEANIC ENGINEERING
Volume 48, Issue 3, Pages 778-788

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2023.3265634

Keywords

Autonomous vehicle navigation; gesture; posture; and facial expressions; sensor-based control; underwater (UW) communication

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Despite the popularity of the buddy system, scuba diving still has significant risks, with a high number of deaths per year. This article suggests a possible solution to the problem by using a dedicated autonomous dive-buddy robot that can also function as an assistant. The challenge lies in how to enable communication and interaction between the diver and the robot in underwater conditions with low visibility. The proposed technological solution involves a smart dive glove that captures finger and hand motions, allowing the diver to send gesture-based commands to the robot.
Despite the popularity of the buddy system, where a pair of divers look out for each other, scuba diving still poses significant risks with 15-30 deaths per 100 000 divers per year. In the 2015 edition of Diving Medicine for Scuba Divers, it is reported that 86% of diving fatalities involve a lone diver, yet divers still elect to dive alone for a variety of reasons including buddy unavailability. A solution to this may lie in a dedicated autonomous dive-buddy robot, which could also operate as an assistant. The challenge is how would the diver interact and communicate with the robot in underwater conditions often involving low visibility. In this article, we detail and demonstrate a technological solution that involves the direct motion capture of fingers and hand using a smart dive glove with integrated stretch sensors alongside an inertial measurement unit. The hardware and gesture recognition protocol were initially evaluated in a lab-based study where 10 users participated in a virtual reality environment setup and interacted with a virtual robot using gestures. In total, 140 out of 175 gestures were correctly recognized, resulting in diver-robot commands. A full sea demonstration of the underwater motion-capture system followed with the underwater dive glove used to send gesture-based acoustic commands to a dedicated dive buddy, a modified autonomous underwater vehicle. The diver was able to command the robot to move in six directions with a total delay of 6 s or less between the beginning of the gesture and the initiation of the action by the robot.

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