Yeshmukhametov, A.; Koganezawa, K.; Yamamoto, Y.; Buribayev, Z.; Mukhtar, Z.; Amirgaliyev, Y. Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes. Applied Sciences 2022, 12, 6922, doi:10.3390/app12146922.
Yeshmukhametov, A.; Koganezawa, K.; Yamamoto, Y.; Buribayev, Z.; Mukhtar, Z.; Amirgaliyev, Y. Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes. Applied Sciences 2022, 12, 6922, doi:10.3390/app12146922.
Yeshmukhametov, A.; Koganezawa, K.; Yamamoto, Y.; Buribayev, Z.; Mukhtar, Z.; Amirgaliyev, Y. Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes. Applied Sciences 2022, 12, 6922, doi:10.3390/app12146922.
Yeshmukhametov, A.; Koganezawa, K.; Yamamoto, Y.; Buribayev, Z.; Mukhtar, Z.; Amirgaliyev, Y. Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes. Applied Sciences 2022, 12, 6922, doi:10.3390/app12146922.
Abstract
Designing and development of agricultural robot is always a challenging issue, because of robot intends to work an unstructured environment and at the same time, it should be safe for the surrounded plants. Therefore, traditional robots cannot meet the high demands of modern challenges, such as working in confined and unstructured workspaces. Based on current issues, we developed a new tomato harvesting wire-driven discrete continuum robot arm with a flexible backbone structure for working in confined and extremely constrained spaces. Moreover, we optimized a tomato detaching process by using newly designed gripper with passive stem cutting function. Moreover, by designing the robot we also developed ripe tomato recognition by using machine learning. This paper explains the proposed continuum robot structure, gripper design, and development of tomato recognition system.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
18 December 2019
Commenter:
Vladimir Berikov
The commenter has declared there is no conflict of interests.
Comment:
The authors present an interesting work on development of tomato harvesting robot which uses pattern recognition system based on deep neural network (YOLO: Real-Time Object Detection system). Compared with other grippers this prototype does not require sensors to control. A lack of electronics allows the robot to work in a wet and highly humid environment. The gripper can cut the tomato with its sepal which helps to increase the storage time for harvested tomatoes. Experiments show the proposed manipulator was slower than commercially available prototypes, however it possesses higher reachability and tomato selectivity.
Received:
24 December 2019
Commenter:
Aigissinova Agipa
The commenter has declared there is no conflict of interests.
Comment:
Interesting paper and a pretty nice technical solution. Well formulated kinematic and kinetic solutions. Harvesting of tomatoes is a very challenging issue, cause of softness, but the proposed gripper seems can handle it easily. Also, an accurately grasping solution is provided. Nice!
Received:
24 December 2019
Commenter:
Khaing Yee Mone
The commenter has declared there is no conflict of interests.
Comment:
Very interesting paper and proposed robot design. Looks like proposed robot can harvest not only tomatoes. Reaching angles to the object infinite. What is the maximum payload capacity?
The commenter has declared there is no conflict of interests.
Comment:
Thank you for your comment.
The maximum payload capacity could be over 220grams but for manipulation, the optimal weight is 175 g. 175 g is more than enough for cherry tomatoes.
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Commenter: Vladimir Berikov
The commenter has declared there is no conflict of interests.
Commenter: Aigissinova Agipa
The commenter has declared there is no conflict of interests.
Commenter: Khaing Yee Mone
The commenter has declared there is no conflict of interests.
Commenter:
The commenter has declared there is no conflict of interests.
The maximum payload capacity could be over 220grams but for manipulation, the optimal weight is 175 g. 175 g is more than enough for cherry tomatoes.