Dynamic Hand Gesture Recognition for Robot Manipulator Tasks

Fuente: arXiv
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Autori principali: Sharma, Dharmendra, Thakur, Peeyush, Gupta, Sandeep, Dhar, Narendra Kumar, Behera, Laxmidhar
Natura: Preprint
Pubblicazione: 2026
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author Sharma, Dharmendra
Thakur, Peeyush
Gupta, Sandeep
Dhar, Narendra Kumar
Behera, Laxmidhar
author_facet Sharma, Dharmendra
Thakur, Peeyush
Gupta, Sandeep
Dhar, Narendra Kumar
Behera, Laxmidhar
contents This paper proposes a novel approach to recognizing dynamic hand gestures facilitating seamless interaction between humans and robots. Here, each robot manipulator task is assigned a specific gesture. There may be several such tasks, hence, several gestures. These gestures may be prone to several dynamic variations. All such variations for different gestures shown to the robot are accurately recognized in real-time using the proposed unsupervised model based on the Gaussian Mixture model. The accuracy during training and real-time testing prove the efficacy of this methodology.
format Preprint
id arxiv_https___arxiv_org_abs_2601_12918
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Dynamic Hand Gesture Recognition for Robot Manipulator Tasks
Sharma, Dharmendra
Thakur, Peeyush
Gupta, Sandeep
Dhar, Narendra Kumar
Behera, Laxmidhar
Robotics
Machine Learning
This paper proposes a novel approach to recognizing dynamic hand gestures facilitating seamless interaction between humans and robots. Here, each robot manipulator task is assigned a specific gesture. There may be several such tasks, hence, several gestures. These gestures may be prone to several dynamic variations. All such variations for different gestures shown to the robot are accurately recognized in real-time using the proposed unsupervised model based on the Gaussian Mixture model. The accuracy during training and real-time testing prove the efficacy of this methodology.
title Dynamic Hand Gesture Recognition for Robot Manipulator Tasks
topic Robotics
Machine Learning
url https://arxiv.org/abs/2601.12918