Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture

Zhaochen Wang; Xiaoyan Gao; Hanling Wang; Yi Chen

doi:10.1007/978-981-99-8498-5_30

Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture

Zhaochen Wang
, Xiaoyan Gao
, Hanling Wang
, Yi Chen^*

^*Corresponding author for this work

School of Intelligent Manufacturing Ecosystem

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

Food security is a pressing issue, particularly considering that approximately one-third of human food consumption depends on animal pollination. However, the decline in natural pollinators threatens the food supply. To address this problem, using micro air vehicle pollinators (MPrs) offers a potential solution by enabling efficient artificial pollination. This study aims to develop an AI algorithm based on the Heredity algorithm for the path planning of autonomous pollination, tailored explicitly for future farming scenarios where robotic MPrs are employed. By doing so, valuable insights can be gained into the autonomous design and manufacturing processes, ultimately leading to increased production efficiency. This research endeavours to bridge the gap between laboratory advancements and market implementation, facilitating a quicker transition and adoption of these technologies.

Original language	English
Title of host publication	Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023
Editors	Andrew Tan, Fan Zhu, Haochuan Jiang, Kazi Mostafa, Eng Hwa Yap, Leo Chen, Lillian J. A. Olule, Hyun Myung
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	379-392
Number of pages	14
ISBN (Print)	9789819984978
DOIs	https://doi.org/10.1007/978-981-99-8498-5_30
Publication status	Published - Aug 2023
Event	International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023 - Suzhou, China Duration: 22 Aug 2023 → 23 Aug 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	845
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023
Country/Territory	China
City	Suzhou
Period	22/08/23 → 23/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

Keywords

Artificial pollination
Food security
Heredity algorithm
Micro air vehicle pollinators
Path planning

Access to Document

10.1007/978-981-99-8498-5_30

Cite this

Wang, Z., Gao, X., Wang, H., & Chen, Y. (2023). Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture. In A. Tan, F. Zhu, H. Jiang, K. Mostafa, E. H. Yap, L. Chen, L. J. A. Olule, & H. Myung (Eds.), Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023 (pp. 379-392). (Lecture Notes in Networks and Systems; Vol. 845). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-8498-5_30

Wang, Zhaochen ; Gao, Xiaoyan ; Wang, Hanling et al. / Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture. Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023. editor / Andrew Tan ; Fan Zhu ; Haochuan Jiang ; Kazi Mostafa ; Eng Hwa Yap ; Leo Chen ; Lillian J. A. Olule ; Hyun Myung. Springer Science and Business Media Deutschland GmbH, 2023. pp. 379-392 (Lecture Notes in Networks and Systems).

@inproceedings{b8729dde2fcb4a4896ed4d41d3c7425f,

title = "Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture",

abstract = "Food security is a pressing issue, particularly considering that approximately one-third of human food consumption depends on animal pollination. However, the decline in natural pollinators threatens the food supply. To address this problem, using micro air vehicle pollinators (MPrs) offers a potential solution by enabling efficient artificial pollination. This study aims to develop an AI algorithm based on the Heredity algorithm for the path planning of autonomous pollination, tailored explicitly for future farming scenarios where robotic MPrs are employed. By doing so, valuable insights can be gained into the autonomous design and manufacturing processes, ultimately leading to increased production efficiency. This research endeavours to bridge the gap between laboratory advancements and market implementation, facilitating a quicker transition and adoption of these technologies.",

keywords = "Artificial pollination, Food security, Heredity algorithm, Micro air vehicle pollinators, Path planning",

author = "Zhaochen Wang and Xiaoyan Gao and Hanling Wang and Yi Chen",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023 ; Conference date: 22-08-2023 Through 23-08-2023",

year = "2023",

month = aug,

doi = "10.1007/978-981-99-8498-5\_30",

language = "English",

isbn = "9789819984978",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "379--392",

editor = "Andrew Tan and Fan Zhu and Haochuan Jiang and Kazi Mostafa and Yap, \{Eng Hwa\} and Leo Chen and Olule, \{Lillian J. A.\} and Hyun Myung",

booktitle = "Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023",

}

Wang, Z, Gao, X, Wang, H & Chen, Y 2023, Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture. in A Tan, F Zhu, H Jiang, K Mostafa, EH Yap, L Chen, LJA Olule & H Myung (eds), Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023. Lecture Notes in Networks and Systems, vol. 845, Springer Science and Business Media Deutschland GmbH, pp. 379-392, International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023, Suzhou, China, 22/08/23. https://doi.org/10.1007/978-981-99-8498-5_30

Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture. / Wang, Zhaochen; Gao, Xiaoyan; Wang, Hanling et al.
Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023. ed. / Andrew Tan; Fan Zhu; Haochuan Jiang; Kazi Mostafa; Eng Hwa Yap; Leo Chen; Lillian J. A. Olule; Hyun Myung. Springer Science and Business Media Deutschland GmbH, 2023. p. 379-392 (Lecture Notes in Networks and Systems; Vol. 845).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture

AU - Wang, Zhaochen

AU - Gao, Xiaoyan

AU - Wang, Hanling

AU - Chen, Yi

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

PY - 2023/8

Y1 - 2023/8

N2 - Food security is a pressing issue, particularly considering that approximately one-third of human food consumption depends on animal pollination. However, the decline in natural pollinators threatens the food supply. To address this problem, using micro air vehicle pollinators (MPrs) offers a potential solution by enabling efficient artificial pollination. This study aims to develop an AI algorithm based on the Heredity algorithm for the path planning of autonomous pollination, tailored explicitly for future farming scenarios where robotic MPrs are employed. By doing so, valuable insights can be gained into the autonomous design and manufacturing processes, ultimately leading to increased production efficiency. This research endeavours to bridge the gap between laboratory advancements and market implementation, facilitating a quicker transition and adoption of these technologies.

AB - Food security is a pressing issue, particularly considering that approximately one-third of human food consumption depends on animal pollination. However, the decline in natural pollinators threatens the food supply. To address this problem, using micro air vehicle pollinators (MPrs) offers a potential solution by enabling efficient artificial pollination. This study aims to develop an AI algorithm based on the Heredity algorithm for the path planning of autonomous pollination, tailored explicitly for future farming scenarios where robotic MPrs are employed. By doing so, valuable insights can be gained into the autonomous design and manufacturing processes, ultimately leading to increased production efficiency. This research endeavours to bridge the gap between laboratory advancements and market implementation, facilitating a quicker transition and adoption of these technologies.

KW - Artificial pollination

KW - Food security

KW - Heredity algorithm

KW - Micro air vehicle pollinators

KW - Path planning

UR - https://www.scopus.com/pages/publications/85187800203

U2 - 10.1007/978-981-99-8498-5_30

DO - 10.1007/978-981-99-8498-5_30

M3 - Conference Proceeding

AN - SCOPUS:85187800203

SN - 9789819984978

T3 - Lecture Notes in Networks and Systems

SP - 379

EP - 392

BT - Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023

A2 - Tan, Andrew

A2 - Zhu, Fan

A2 - Jiang, Haochuan

A2 - Mostafa, Kazi

A2 - Yap, Eng Hwa

A2 - Chen, Leo

A2 - Olule, Lillian J. A.

A2 - Myung, Hyun

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023

Y2 - 22 August 2023 through 23 August 2023

ER -

Wang Z, Gao X, Wang H, Chen Y. Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture. In Tan A, Zhu F, Jiang H, Mostafa K, Yap EH, Chen L, Olule LJA, Myung H, editors, Advances in Intelligent Manufacturing and Robotics - Selected Articles from ICIMR 2023. Springer Science and Business Media Deutschland GmbH. 2023. p. 379-392. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-99-8498-5_30

Path Planning of Autonomous Pollination Using Heredity Algorithm for Intelligent Agriculture

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this