Robotic Detection of a Human-Comprehensible Gestural Language for Underwater Multi-Human-Robot Collaboration

Enan, Sadman Sakib; Fulton, Michael S.; Sattar, Junaed

doi:10.1109/iros47612.2022.9981450

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…Addressing the critical aspect of safety, researchers have explored visual detection methods to gauge diver attentiveness. This innovative approach aims to bolster safety during underwater interactions by enabling robots to perceive and react to the attention levels of human divers, thereby minimizing the risk of accidents and fostering a safer operational atmosphere [20].…”

Section: Hri In Underwater Roboticsmentioning

confidence: 99%

“… Innovative Approach to Gesture Recognition Systems: Recent developments in visual detection systems that assess diver attentiveness highlight the critical need for gesture recognition solutions that are straightforward and dependable. Such advancements could greatly enhance underwater task safety and efficiency by ensuring precise interpretation of divers' gestures by robots [17,20].  Enhancing Interfaces for Robot Teleoperation: As the field of underwater robotics evolves, optimizing the design of human-robot interfaces for teleoperation becomes crucial.…”

Section: Future Directionsmentioning

confidence: 99%

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Integrating augmented reality, gesture recognition, and NLP for enhancing underwater human-robot interaction

Durga Deepak Valluri

2024

Int. J. Sci. Res. Arch.

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This paper presents an in-depth exploration into the integration of augmented reality (AR), gesture recognition, and natural language processing (NLP) to enhance human-robot interaction (HRI) within the context of underwater robotics. It highlights the significant potential these technologies hold in addressing the unique challenges faced in underwater environments, such as limited visibility, complex navigation, and the need for precise, intuitive communication between divers and robots. By reviewing current technological advancements and applications, the study underscores the critical role of AR in providing real-time visual feedback, gesture recognition in enabling more natural control mechanisms, and NLP in facilitating voice-driven commands and interactions. The research further discusses the development of a conceptual framework for an AR-based intuitive interface that synergizes gesture recognition and NLP, aiming to revolutionize underwater HRI by making it more efficient, safe, and user-friendly. Through this investigation, the paper seeks to contribute to the advancement of underwater robotics, proposing innovative solutions that could significantly improve human-robot collaboration in challenging aquatic missions.

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Section: Hri In Underwater Roboticsmentioning

confidence: 99%

Section: Future Directionsmentioning

confidence: 99%

Integrating augmented reality, gesture recognition, and NLP for enhancing underwater human-robot interaction

Durga Deepak Valluri

2024

Int. J. Sci. Res. Arch.

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“…The language has a limited set of commands (about eleven) and is more suitable for recreational diving as it does not provide messages to communicate an emergency and also requires the use of both hands for communication, which during a professional dive is no small constraint. The same year, Fulton et al [39,40] proposed an interesting approach for underwater robot-to-human communication via robot motion: every motion, called a kineme, is associated with a distinct meaning (i.e., head shake (yaw) = no).…”

Section: Related Workmentioning

confidence: 99%

Towards Multi-AUV Collaboration and Coordination: A Gesture-Based Multi-AUV Hierarchical Language and a Language Framework Comparison System

Chiarella

2023

JMSE

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The underwater environment is a harmful environment, yet one of the richest and least exploited. For these reasons the idea of a robotic companion with the task of supporting and monitoring divers during their activities and operations has been proposed. However, the idea of a platoon of robots at the diver’s disposal has never been fully addressed in these proposals due to the high cost of implementation and the usability, weight and bulk of the robots. Nevertheless, recent advancements in swarm robotics, materials engineering, deep learning, and the decreasing cost of autonomous underwater vehicles (AUVs), have rendered this concept increasingly viable. Therefore, this paper introduces, in the first part, a novel framework that integrates a revised version of a gesture-based language for underwater human–robot interaction (Caddian) based on insights gained from extensive field trials. The newly introduced objective of this framework is to enable the cooperation and coordination of an AUV team by one or more human operators, while allowing a human operator to delegate a robot leader to instruct the other robotic team members. The work, in the second part, provides an evaluation of the new language proposed thanks to a fifty million sentence corpus and describes a comparison framework, which is used to estimate it with respect to other existing underwater human–robot interaction languages.

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Intuitive Multi-modal Human-Robot Interaction via Posture and Voice

Lai,

Radke,

Nassar

et al. 2024

Communications in Computer and Information Science

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Robotic Detection of a Human-Comprehensible Gestural Language for Underwater Multi-Human-Robot Collaboration

Cited by 6 publications

References 37 publications

Integrating augmented reality, gesture recognition, and NLP for enhancing underwater human-robot interaction

Integrating augmented reality, gesture recognition, and NLP for enhancing underwater human-robot interaction

Towards Multi-AUV Collaboration and Coordination: A Gesture-Based Multi-AUV Hierarchical Language and a Language Framework Comparison System

Intuitive Multi-modal Human-Robot Interaction via Posture and Voice

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