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Human–Robot Interaction through Dynamic Movement Recognition for Agricultural Environments

Authors :
Vasileios Moysiadis
Lefteris Benos
George Karras
Dimitrios Kateris
Andrea Peruzzi
Remigio Berruto
Elpiniki Papageorgiou
Dionysis Bochtis
Source :
AgriEngineering, Vol 6, Iss 3, Pp 2494-2512 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In open-field agricultural environments, the inherent unpredictable situations pose significant challenges for effective human–robot interaction. This study aims to enhance natural communication between humans and robots in such challenging conditions by converting the detection of a range of dynamic human movements into specific robot actions. Various machine learning models were evaluated to classify these movements, with Long Short-Term Memory (LSTM) demonstrating the highest performance. Furthermore, the Robot Operating System (ROS) software (Melodic Version) capabilities were employed to interpret the movements into certain actions to be performed by the unmanned ground vehicle (UGV). The novel interaction framework exploiting vision-based human activity recognition was successfully tested through three scenarios taking place in an orchard, including (a) a UGV following the authorized participant; (b) GPS-based navigation to a specified site of the orchard; and (c) a combined harvesting scenario with the UGV following participants and aid by transporting crates from the harvest site to designated sites. The main challenge was the precise detection of the dynamic hand gesture “come” alongside navigating through intricate environments with complexities in background surroundings and obstacle avoidance. Overall, this study lays a foundation for future advancements in human–robot collaboration in agriculture, offering insights into how integrating dynamic human movements can enhance natural communication, trust, and safety.

Details

Language :
English
ISSN :
26247402
Volume :
6
Issue :
3
Database :
Directory of Open Access Journals
Journal :
AgriEngineering
Publication Type :
Academic Journal
Accession number :
edsdoj.40270bd3eae433d8d73d9156ebbf40b
Document Type :
article
Full Text :
https://doi.org/10.3390/agriengineering6030146