Advanced Control, Automation and Robotics

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 2339

Special Issue Editor

School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
Interests: flight control; intelligent decision-making; advanced navigation

Special Issue Information

Dear Colleagues,

2022 International Conference on Advanced Control, Automation and Robotics (ICACAR 2022) will be held in Guangzhou, China on March 26–28, 2022.

The International Conference on Advanced Control, Automation, and Robotics (ICACAR 2022) aims to bring together researchers, engineers, scientists and industry professionals in areas related to advanced control, automation and robotics in a single platform and to present their stimulating research and knowledge transfer ideas in both advanced control, automation, and robotics. Leading researchers and industry experts from around the globe will present the latest studies through oral or poster presentations. ICACAR 2022 welcomes new research in the areas of advanced control, automation, and robotics, such as intelligent control systems and optimization, robotics and automation, signal processing, sensors, systems modeling and control, industrial engineering, production, management, and artificial intelligence. However, we also recognize that the future of advanced control, automation, and robotics scientists and engineers is one where they will be working in interdisciplinary teams to solve new, complex, and evolving problems that will require innovative solutions. Therefore, we encourage the participation of other disciplines in this conference, at which multidisciplinary research and knowledge transfer projects will be presented.

The authors of a number of selected full papers of high quality will be invited after the conference to submit revised and extended versions of their originally accepted conference papers to this Special Issue of Information, published by MDPI in open access. The selection of these best papers will be based on their ratings in the conference review process, quality of presentation during the conference, and expected impact on the research community. For each submission to this Special Issue, at least 50% of the content should be new material, e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases, and there should be a change of title, abstract, and keywords. These extended submissions will undergo a peer review process according to the journal’s rules of action. At least two technical committees will act as reviewers for each extended article submitted to this Special Issue; if needed, additional external reviewers will be invited to guarantee a high-quality reviewing process.

Prof. Dr. Bin Xu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

18 pages, 4771 KiB  
Article
An Improved Complete Coverage Path Planning Method for Intelligent Agricultural Machinery Based on Backtracking Method
by Yonglian Han, Min Shao, Yunzhi Wu and Xiaoming Zhang
Information 2022, 13(7), 313; https://0-doi-org.brum.beds.ac.uk/10.3390/info13070313 - 27 Jun 2022
Cited by 5 | Viewed by 1883
Abstract
The advancement of society and technology has promoted the development of modern agriculture. It has become a trend to replace traditional manpower with intelligent agricultural machinery that operates independently. As the core technology of intelligent agricultural machinery, complete coverage path planning technology has [...] Read more.
The advancement of society and technology has promoted the development of modern agriculture. It has become a trend to replace traditional manpower with intelligent agricultural machinery that operates independently. As the core technology of intelligent agricultural machinery, complete coverage path planning technology has become more important. At present, the complete coverage path planning algorithms still suffer from problems such as sacrificing the coverage rate to obtain the minimum energy consumption, taking a long time to calculate the algorithm, and destroying crops across the covered region. In view of the above problems, an improved complete coverage path planning algorithms based on backtracking is proposed combined with the actual needs of intelligent agricultural machinery for planting seedlings to improve four aspects: repeated coverage, search efficiency, path planning, and sub-regional crossing. Firstly, the Morse decomposition method is used to divide a complex farmland region into simple sub-regions. Then an improved backtracking method based on a greedy algorithm is proposed in order to reduce the computational efficiency of the current region connection algorithms. The priority principle and the strategy of moving along the boundary are used to solve the problems of region crossing and sacrificing the coverage rate, thereby improving the performance of the current complete coverage path planning method. Compared with the traditional backtracking method, the experimental results show that the number of backtracking points is decreased by about 70% and the occurrence of crossing sub-regions has been significantly reduced. This proposed method can improve the coverage and operating efficiency of intelligent agricultural machinery operations and provide technical support for agricultural operations such as sowing, tillage, and harvesting, thus improving the quality and efficiency of agricultural production. Full article
(This article belongs to the Special Issue Advanced Control, Automation and Robotics)
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