Design and development of a peduncle-holding end effector for robotic harvesting of mango

Mango harvesting remains predominantly manual despite technological advances in agriculture. Traditional manual harvesting methods are labour-intensive and often result in mechanical injuries, bruising, and sap-induced infections, leading to reduced fruit quality and market value. This study presents the development of a specialized end effector for robotic mango harvesting. The developed end effector is capable of simultaneously cutting and grasping the mango peduncle, maintaining fruit integrity while minimizing mechanical injuries, bruising, and sap-induced infections. Its compact and modular design enhances maneuverability and operational efficiency, providing a secure grip on mangoes during cutting and transport until release in the conveying unit, ensuring the harvested fruit remains undamaged and market-ready. Initially inspired by handheld tools, the design evolved from using a net bag to finger grippers, and finally, a compact unit with integrated pads, capable of cutting and holding the fruit simultaneously. The design process involved conceptualizing and evaluating three designs, with the most efficient one being fabricated and tested. The end effector operates using a single servo motor for both cutting and grasping the peduncle. In lab trials, it successfully picked 17 mangoes at a rotational speed of 105 rad/s. The developed end effector achieved a conveying efficiency of approximately 96.7% with only 2 out of 60 mangoes falling from it during the lab trials. The performance evaluation demonstrated the end effector’s ability to consistently harvest mangoes with minimal failures, validating its practicality and robustness.

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Publication Details

Journal
Cogent Engineering
Published
2024-09-19
DOI
https://doi.org/10.1080/23311916.2024.2403706
Citations
5
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
3.00
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article

Design and development of a peduncle-holding end effector for robotic harvesting of mango

Abhishek Ranjan, Prakhar Patidar, Rajendra Machavaram
5 citations
Cogent Engineering
Smart Agriculture and AI
3.00
article

Design and development of a peduncle-holding end effector for robotic harvesting of mango

Abhishek Ranjan, Prakhar Patidar, Rajendra Machavaram
article en
5 citations

Abstract

Mango harvesting remains predominantly manual despite technological advances in agriculture. Traditional manual harvesting methods are labour-intensive and often result in mechanical injuries, bruising, and sap-induced infections, leading to reduced fruit quality and market value. This study presents the development of a specialized end effector for robotic mango harvesting. The developed end effector is capable of simultaneously cutting and grasping the mango peduncle, maintaining fruit integrity while minimizing mechanical injuries, bruising, and sap-induced infections. Its compact and modular design enhances maneuverability and operational efficiency, providing a secure grip on mangoes during cutting and transport until release in the conveying unit, ensuring the harvested fruit remains undamaged and market-ready. Initially inspired by handheld tools, the design evolved from using a net bag to finger grippers, and finally, a compact unit with integrated pads, capable of cutting and holding the fruit simultaneously. The design process involved conceptualizing and evaluating three designs, with the most efficient one being fabricated and tested. The end effector operates using a single servo motor for both cutting and grasping the peduncle. In lab trials, it successfully picked 17 mangoes at a rotational speed of 105 rad/s. The developed end effector achieved a conveying efficiency of approximately 96.7% with only 2 out of 60 mangoes falling from it during the lab trials. The performance evaluation demonstrated the end effector’s ability to consistently harvest mangoes with minimal failures, validating its practicality and robustness.

Cogent EngineeringVol. 11(1)
Indian Institute of Technology Kharagpur (IN)
Openalex Percentile: Top 9%
Smart Agriculture and AI
3.00
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