Workshops
01

Multi-mode Data Processing, Information Analysis, Complex Networks, Large Language Model and Information Service Application

Chair:
Assoc. Prof.  Sheng Hong, School of Cyber Science and Technology , Beihang University, China
Sheng Hong is an associate professor and doctoral supervisor in the School of Cyber Science and Technology at the Beihang University (BUAA). He engaged in network and information security, complex system security research, antagonistic sample generation technology, deep learning, generative adversarial network, completed a number of related scientific research projects in the field of network security, Presided over the national key basic research and development plan projects, national key research and development project, industrial Internet innovation and development project, technical basic project, pre-research project, National Natural Science Foundation of China There are more than 10 national, provincial and ministerial-level topics, and more than 10 horizontal topics in key industries such as industrial Internet, intelligent manufacturing, State Grid, and avionics systems. He is the editorial board member of several international journals and conferences, including "Information Network Security", "Information Technology and Network Security" and "Aeronautical Engineering Progress". In the national key research and development plan, he established a multi-level industrial network security protection model, through dangerous targets, key targets, cloud detection and other protection strategies and protective measures to ensure the network from the aspects of environmental credibility, situational knowledge, and controllable operation. Security; in the industrial Internet innovation and development project, he proposed a system security enhancement protection technology for the industrial Internet; in the National Natural Science Foundation, he broke through the critical phase change mechanism of fault propagation by focusing on the coupling, chaos and spreading characteristics of dynamic network faults The bottleneck of the maintenance control strategy provides a new solution for the prevention of complex dynamic network fault propagation and fault-tolerant control. In the open topic of the Shanghai industrial control system safety innovation functional platform, he aimed at the industrial Internet network suffered from virus attacks and equipment paralysis. The actual problems of the research network virus transmission mechanism and protection strategies. He has published more than 70 papers, including 30+ SCI papers, one co-authored academic book, and 14 national invention patents.

Summary:
The research is mainly aimed at the demand for new quality and new domain information services in the fields of science and technology, industry and informatization, scientific and technological innovation entities, and the public's scientific and technological information. Based on the open source data acquisition technology, multilingual and multimodal scientific and technological intelligence content identification, heterogeneous scientific and technological intelligence information fusion, intelligence reasoning and analysis platform research, complex networks and complex systems, social networks, large language model and information service application. Focusing on multi-mode technology competitiveinformation tracking and cutting-edge trend analysis, the research mainly forms scientific and technological information service solutions and demonstration system platforms for different users and fields, and carries out application demonstration around strategic cutting-edge (choke) scientific and technological development support, commercial scientific and technological innovation services, public welfare scientific and technological intelligence information query services, etc. in the fields of science and technology, industry and informatization.
* Multi Source Data Collection
* Data Fusion and Data Analysis
* Intelligence Knowledge Extraction
* Scenario Construction
* Demonstration and Promotion
* Complex Networks and Complex Systems
* Social Networks
* Large Language Model
* Information Service Application

Keywords:
Technical Competitive Information, Application Demonstration, Multi-source Information Fusion,Complex Networks, Complex Systems, Social Networks
02

Intelligent Robot:
Intelligent Robot Design and Control Algorithm

Chair:
Dr. Xiaoqing Zhu, Beijing University of Technology, China 
Xiaoqing Zhu received a Ph.D. degree in Control Science and Technology from Beijing University of Technology. He is a master tutor at Beijing University of Technology, he also served as Deputy Secretary General of the Beijing Association of Artificial Intelligence, Committee member of the integrated robot Committee of the Chinese Society of Automation, and Committee member of the Science Popularization Committee of the Chinese Society of Artificial Intelligence. His research interests include intelligent robot design and machine learning. He has presided over 5 national or provincial projects with National Natural Science Foundation of China, and Beijing Natural Science Foundation. Based on these projects, he has published more than 30 papers and over 15 patents, he won the second prize of Wenjun WU AI Science and Technology Award on Technological Invention Award.

Summary:
Intelligent Robots are becoming more and more important in national life. The design and control theory of robots is a research hotspot at home and abroad. As a typical representative in the field of artificial intelligence, intelligent robot can symbol a country's artificial intelligence and even the level of science and technology to a certain extent. Especially for the service robot, it can perform certain tasks and help people complete dangerous or repetitive work, it is very valuable to study the design theory and control method of service robot. Researchers at home and abroad get inspiration from nature and make creative improvements to complete the structural design and control algorithm of the robot. The skill learning of the service robot mainly focuses on two aspects, one is its basic motion skills, and the other is its operation skills. 
The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of intelligent robot design and understand how control strategy can influence it. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.

Keywords:
Intelligent Robot, Service Robot, Control algorithm, Machine Learning, Skill Learning
03

Modeling, Perceptionand Intelligent Cluster Control of 
Bionic Robots


Chair:
Assoc. Prof. Keqiang BaiSouthwest University of Science and Technology, China 
Keqiang Bai, PhD. associate professor, Master native tutor, Member of Chinese Society for Artificial Intelligence, Member of Chinese Society for Simulation. Since 2007, he has been engaged in robot control teaching and research work. In 2014, he studied with Minzhou Luo, Institute of Advanced Manufacturing Technology, Hefei Institute of Physical Science, Chinese Academy of Sciences, and carried out long-term cooperation in the application research of humanoid robot. In 2017, he majored in control science and Engineering at the Department of Automation, University of Science and Technology of China. Doctor of Engineering. At present, he isin charge of robot technology and control system and intelligent control algorithm in the Advanced Control and Modeling Laboratory of Southwest University of Science and Technology. This major is mainly devoted to the research of robot motion planning, motion control and controller development, and high-altitude simulation test of aviation engines. He has published more than 40 academic papers, including 11 SCI journals, 5 EI papers and 2 conference papers in the field of robotics. In recent years, he participated in 1 major special "intelligent robot" project of the Ministry of Science and Technology, 2 projects of the National Natural Science Foundation, 1 project of Jiangsu Province Science and Technology Support Fund, presided over 1 project of the Equipment Development Department of the Central Military Commission, 1 project of China Aviation Development Group, 1 project of Sichuan Province Science and technology Application Basic Research project, 1 science and Technology project of Sichuan Province Education Department, and 1 doctoral fund of Southwest University of Science and Technology To a number of subjects. He has been engaged in the teaching and research of bionic robot, aeroengine simulation test, control theory and control engineering, intelligent control technology and system identification.

Summary:
In recent years, special dangerous environments such as outer space exploration, rescue and disaster relief, high radiation , and military reconnaissance are not suitable for human safety work. Robots cooperate with each other to form a formation cluster, which can give play to the advantages that a single robot does not have, and be more competent for work in complex and multi-task scenarios. This makes people continue to study robot technology and replace humans with robots to complete arduous tasks. Therefore, it is of great value to society to develop accurate and reliable bionic robots and intelligent cluster control algorithms. The accurate modeling of the bionic robot can provide a relatively accurate mathematical model for the control algorithm. The research on perception of bionic robots can provide real-time environment information for robots and lay a foundation for intelligent control. Intelligent control algorithm is used to carry out experiments in a large scene and multi-robot environment to improve the efficiency and safety of multi-robot collaborative work. The combination of control algorithm and artificial intelligence can significantly improve the cluster control efficiency of bionic robots.
The symposium aims to bring together research results from researchers in academia and industry. Another goal is to present the latest research results in the field of modeling, sensing and intelligent cluster control of bionicrobots, and to understand how sensing methods and control strategies affect them. We encourage prospective authors to submit outstanding research papers related to topics: theoretical methods and experimental validation.

Keywords:
Bionic Robot, Robot Arm, Control Algorithm, Cluster Control, Robot Perception
04

Cooperative Multi-robot Learning 
and Control


Chair:
Dr. Eng. Gembong Edhi SetyawanBrawijaya University, Indonesia
Gembong Edhi Setyawan serves as lecture at the Computer Engineering Program Study, Informatic Engineering Department, Computer Science Faculty, Brawijaya University in Indonesia. He received the B.Eng. degree from the Electrical Engineering Department, Brawijaya University in Indonesia, the M.Eng. degree from the Electrical Engineering Department, Sepuluh Nopember Institute of Technology (ITS) in Indonesia, and the Dr. Eng. Degree from the Pure and Applied Physics Department of Waseda University in Japan. He is currently invited as an editor and reviewer for numerous international journals and conferences, e.g., Founder and Managing Editor in the Journal of Information Technology and Computer Science (JITeCS), Advisory board in the International Conference on Sustainable Information Engineering and Technology (SIET), Associate editor in the Network: Computation in Neural System, reviewer in the Journal of Computational Science, reviewer in theISA Transactions, etc. His primary research interests are reinforcement learning theory and applications, cooperative muti-robot, and intelligent robotic control. Based on these primary research interests, he published many academic papers.

Summary:
Multi-Robot Systems (MRS) are believed to be more beneficial to Single-Robot Systems (SRS) in their ability to solve complex problems. MRS provides advantages including increased resistance to possible failures, flexibility in task execution, and collective information exchange. In addition, MRS can distribute work to multiple robots and make it easier each robot's task. However, the challenge of utilizing MRS is that robots must be able to cooperate and coordinate to manage each task assigned to each robot as a solution to the main problem. In recent years, there has been an increased interest in the utilization of multi-robot learning techniques for controlling the behaviour of robots so that they cooperate in solving complex problems. Reinforcement learning is one of the most popular learning techniques for multi-robot control. The improvement of Reinforcement Learning is always challenged by an issue known as the curse of dimensionality. With Deep Reinforcement Learning (DRL) and Hierarchical Reinforcement Learning (HRL), researchers are attempting to solve these issues.
This workshop aims to discuss the most recent research findings in the field of MRS and the innovation of controlling and learning algorithms for MRS. We encourage prospective authors to submit outstanding research papers on the following topics: theoretical methods and experimental validation.

Keywords:
Cooperative, Multi-robot System, Learning, Control System, Reinforcement Learning
05

Intelligent Perception of Robots


Chair:
Assoc. Prof. Feng XuSouthwest University of Science and Technology, China
Feng Xu, doctor, associate professor, master's supervisor, member of China artificial intelligence society and China computer federation.he received a Ph.D. degree in measurement technology and instruments in the Institute of Optics and Electronics of the Chinese Academy of Science. At present, in the School of Information and Engineering of Southwest University of Science and Technology, he has been engaged in the research of machine vision andintelligent perception of robots for a long time, especially in the scene perception of robot, object detection, image understanding, robot SLAM, etc. He has presided over or mainly completed 17 scientific research projects, including 2 National Natural Science Foundation of China, 2 projects ofState Administration of Science, Technology and Industry for National Defense, 3 projects of Science and Technology Department of Sichuan Province.More than 30 academic papers have been published, including 12 papers in SCI journals, 10 papers in EI, more than 10 invention patents have been declared and authorized.

Summary:
With the rapid development of sensing and detection technology and artificial intelligence technology, robots are gradually moving from traditional industrial fields to more extensive application fields such as agricultural harvesting, household services, public medical care, warehousing and logistics, and space exploration. In recent years, robots have played an important role in various fields and become the core tooling of high-end equipment and intelligent manufacturing. However, due to the insufficient perception ability of robots in unstructured application environments, the task adaptability and application scope of robots are seriously restricted. 
In terms of robot perception, researching robot multi-sensor information fusion algorithms and effectively using visual sensors, lidar, radar, ultrasonic sensors, etc. to obtain rich perception information is the basis for realizing robot multi-source perception collaboration. This is also the key to improving the robot's ability to perceive unstructured environments and novel targets, and it is also important to improve the dexterity of the robot. 
The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of robot perception. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.

Keywords:
Multi-Sensor Information Fusion; Intelligent Perception; Self-Localization; Scene Mapping
06

Communication and Detection Technologies for
Underwater Intelligent Robots

Chairs:

Prof. Meiwei KongTongji University, China
Meiwei Kong is a Research Fellow at the State Key Laboratory of Marine Geology, School of Ocean and Earth Science, Tongji University. She received the Ph.D. degree in marine information science and engineering from Zhejiang University, China in 2018. During 2018–2021, She was a Postdoctoral Research Fellow at Photonics Laboratory in the Division of Computer, Electrical and Mathematical Sciences & Engineering at King Abdullah University of Science and Technology. Her research interests are digital signal processing, indoor/underwater optical wireless communication system and network design, and wireless power transfer. She is the author or co-author of over 50technical papers published in scientific journals or presented at international conferences.


Assoc. Prof. Ruizhi Wang, Tongji University, China
Ruizhi Wang is an associate professor in the College of Electronics and Information Engineering at the Tongji University. She is a committee member of the Professional Committee of Granular Computing and Knowledge Discovery of Chinese Association for Artificial Intelligence(CAAI). Her research interests include Machine Learning and Granular Computing. She participated in 7 national projects with National Natural Science Foundation of China. She has published more than 40 papers and won the second prize of WU WEN JUN AI SCIENCE & TECHNOLOGY AWARD (2018).


Dr. Xiaoxiao Zhuo, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, China
Xiaoxiao Zhuo is a Post-Doctoral Researcher at the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China. She received the B.E. degree in Information Science and Electronic Engineering and Ph.D. degree from Zhejiang University in 2017 and 2022, respectively.During 2021-2022, she was a Visiting Ph.D. Student with the Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada. Her current research interests include media access control protocols, cross-layer design, and resource management for underwater acoustic communication networks. She has published more than 10 academic papers. She served as the TPC Co-chair of the VTC-Fall 2023 and served as the reviewer of IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, etc.

Summary:
In recent years, underwater robots have shown good application prospects in various marine activities, such as marine environmental monitoring, marine resource exploitation, marine disaster prediction, and marine rescue. However, due to the lack of communication and detection capabilities, underwater robots are not intelligent enough, which seriously restricts their task adaptability and application scope. Improving the ability of underwater robots in high-speed and real-time underwater wireless optical communication, long-distance underwater acoustic communication, and high-precision underwater optical target detection is of great significance for the realization of underwater intelligent robots.
The aim of this workshop is to bring together the research accomplishments provided by researchers from academia and the industry.The other goal is to show the latest research results in the field ofunderwater wireless optical communication, underwater acoustic communication, underwater optical target detection, and underwater acquisition, pointing and tracking. The topics in this workshop include but are not limited to the above. We encourage prospective authors to submit related distinguished research papers on the subject.

Keywords:
Underwater wireless optical communication; Underwater acoustic communication; Underwater optical target detection; Underwater acquisition, pointing and tracking; Underwater intelligent robots.
07

Artificial Intelligence & Intelligent Manufacturing
& Interdisciplinary

Chair:

Prof. Xianbo SunHubei Minzu University, China
Xianbo Sun received a Ph. D. degree in traffic information engineering and control at Wuhan University of technology. He has been engaged in the teaching and research of control theory and control engineering, industrial automation, Internet of things and other disciplines for a long time. He published more than 30 papers in academic journals, including 10 papers indexed by SCI, 8 papers indexed by EI and 1 monograph. He presided over and completed 1 project supported by National Natural Science Foundation of China, 4 provincial projects, 6 Enterprise scientific research projects. He owns more than 10 national invention patents, utility model patents and software copyrights.He Received the second prize of the Hubei Provincial Science and Technology Progress Award once, Received the second Youth Science and Technology Award from Enshi Prefecture.

Summary:
This workshop aims to bring together researchers from multiple engineering disciplines, including computer, electrical, communications, mechanical, and systems engineering, who focus their efforts on understanding AI-specific issues, such as perception, planning, and control, and powerful and reliable end-to-end autonomous integration. Objectives include an overview of the major research challenges in the field, cross-collaboration between AI researchers and experts in engineering design and manufacturing, and an overview of open issues of common interest.

Keywords:
Artificial Intelligence, Intelligent perception, Intelligent Manufacturing, Interdisciplinary
08

Quality Inspection in Food Industry Using AI

Chair:

Assoc. Prof. Syed Sumera Ali CSMSS Chh. Shahu College of Engineering, Aurangabad, Maharashtra, India
Dr. Syed Sumera Ali works as Associate Professor in Electronics & Computer Engineering Department at CSMSS Chh. Shahu College of Engineering, Aurangabad, Maharashtra, India. She has 15 years' of teaching & research experience. She Pursued Ph.D (Electronics & Telecommunication Engineering) from Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, and Maharashtra, India. MTech (Digital System & Computer Electronics) from Jawaharlal Nehru Technological University, Hyderabad, Telangana, India, B.E. (E&TC) from Swami Ramanand Teerth Marathwada University Nanded, India. Diploma (Electrical Engineering) from Govt. Polytechnic, Nanded India. She has worked under four university SRTMU, JNTU, DBAMU & DBATU Universities. She has published four books. She has published 30+ research papers in International/National journals & Conferences, Acting as reviewer & Conference Advisory Committee Member in reputed journals. She has delivered many sessions on career guidance & parenting in schools. She is member of professional bodies IETE, IEI, ISTE, ISOI, BMEI & AMP. She has a receipt of various Excellence Academic Awards.

Summary:
In this paper, food quality ranking process was developed by using Enhanced region growing segmentation and MLP-WOA technique has been used for the classification process. Initially, input database images are pre-processed by the histogram equalization technique. After ERG segmentation process is used to isolate several segmented database images. Later MLP-WOA classifier helps in ranking of food products. Further, the numerical results regarding sensitivity, specificity, accuracy and error were determined for several methods namely MLP-GA, MLP-PSO,MLP-FA, MLP-ABC and the performance metrics were compared with our proposed MLP-WOA technique. From this evaluation we conclude that our proposed method has high accuracy with minimum mean square error. AI drives innovation in the food industry. From improving supply chain and food sorting to maintaining food safety compliance, quality control, cleanliness, and food delivery efficiency, processing time and providing helpful information about food quality. AI can redefine food inspection industry & AI quality control in manufacturing can determine optimal operating conditions. By analyzing various production data. Thus, defects and product waste are minimized. AI can challenge the food industry by minimizing human error. The role of AI in food business inspection industry are many more, Sector-specific solutions, Food security, Supply constraints, Food waste has increased, Increasing prices.

Keywords:
AI, Food Inspection IndustryComputer Vision, MLP Neural Network classifier, Whale Optimization Algorithm
09

Intelligent Actuation and Multi-mode Biomimetic Robotics

Chairs:

Assist. Prof. Jiajun XuNanjing University of Aeronautics and Astronautics, China
Dr. Jiajun Xu is an assistant professor and master supervisor in Nanjing University of Aeronautics and Astronautics, China. He received the Ph.D. degree from University of Science and Technology of China and City University of Hong Kong concurrently in 2021. He has been working as an assistant professor in the College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics since July 2021. His research interests include rehabilitation robotics, biomedical robotics, biomimetic robotics, human-robot interaction, soft robotics, smart material actuation, and artificial intelligence. He has hosted or participated in more than 10 national or provincial research projects, published more than 30 SCI/EI papers in high-level journals or conferences, and applied for or authorized more than 30 national patents. He won the Best Paper Award Finalist of 2019 ICMA (IEEE International Conference on Mechatronics and Automation), Winner Award of the Chinese Academy of Sciences "First Cup" Future Technology Innovation Competition, China Aerospace Science and Technology Corporation (CASC) Postgraduate Scholarship, Guanghua Scholarship, etc. In 2022, he was selected into the "Double Creation Doctor" Talent Plan of Jiangsu Province. Also, he was awarded the Merit-Based Funding of the Nanjing Science and Technology Innovation Project for Overseas Scholars. He has served as a reviewer for many journals or conferences such as IEEE Transactions, ISA Transactions, IEEE Systems Journal, IEEE RAL, ICRA, IROS, and ROBIO.


Assist. Prof. Yumo Wang, Nanjing University of Science and Technology, China
Yumo Wang received the Ph.D. degree in precision machinery and precision instrumentation from University of Science and Technology of China (USTC). He is an assistant professor at Nanjing University of Science and Technology, and an expert consultant for the first batch of unmanned aerial test zones in China. He has won the China Youth Science and Technology Innovation Award (the highest honor encouraging youth science and technology innovation activities), Hainan Youth May Fourth Medal, Stars of Self-improvement of Chinese College Students, and Meritorious Winner of the Mathematical Contest In Modeling (MCM/ICM). He has founded 3 technology enterprises. He has served as a team leader and won more than 10 national level awards such as the national silver medal of China College Students' “Internet+” Innovation and Entrepreneurship Competition. He has also won more than 20 provincial-level honors such as Double Creation Doctor Talent Plan of Jiangsu Province, the Gold Award in Anhui Province College Student Entrepreneurship Competition and Outstanding Graduates in Anhui Province. He has been awarded from national leaders at the Great Hall of the People in Beijing. His research results and personal achievements have been reported by the People's Daily. In 2016, he has been awarded the Hainan Youth May Fourth Medal and became one of the youngest recipients (aged 21), he was also the only student selected in the province. He has been engaged in the teaching and research of bio-inspired robots, smart materials and their applications, vertical takeoff and landing un-manned aerial vehicle, and medical detections based on artificial intelligence. Based on these projects, he has published more than 10 papers and over 20 patents.

Summary:
Recent research in robotics has focused on intelligent actuation and multimodal biomimetic robots. Smart material-based actuators possess the advantages of high precision, fast response, varying motions, efficient energy, and greatstability.Smart material-based actuators, such as piezoelectric actuators, shape memory alloy-based actuators, and dielectric elastomer actuators, are facilitating the development of robotics, mechatronic system, bio-operation devices, and other fields. Biomimetic robotics, inspired by nature, robots are developed to mimic the behavior and capabilities of living organisms, enhancing adaptability and functionality. Based on this, benefitingfrom variable mechanical structures, diverse control methods, andmultimodal perception systems, multi-mode biomimeticrobots can be applied into many fields, ranging from industrial automation to medical applications, with gathering accurate environmental information and adapting locomotion modes. 
The aim of this workshop is to bring together researchers from academia and industry to share their research accomplishments and discuss the latest advancements in intelligent actuation and multi-mode biomimetic robotics. Topics of interest for this workshop include but are not limited to: novel actuation mechanisms for intelligent robots, robots actuated by smart materials, multimodal mechanical structure and control strategy, bioinspiredapproaches for robot design and implementation, integration of multi-modal sensing technologies, applications of intelligent actuation and biomimetic robotics in extreme environment, etc.
We encourage prospective authors to submit distinguished research papers on any of the above topics or related areas. The workshop will provide a platform to exchange ideas, collaborate, and pave the way for future breakthroughs in intelligent actuation and multi-mode biomimetic robotics.

Keywords:
Intelligent material;Actuation control;Multi-modal perception;Bioinspired structure; Biomimetic robotics; Soft robotics; Robotics science and technology; Bionic engineering; Machine learning
10

Motion Planning for Mobile Robots

Chairs:

Prof. Xiangrong XuAnhui University of Technology, China
Xiangrong Xu (Member, IEEE) currently is a professor in the School of Mechanical Engineering at the Anhui University of Technology, Ma'anshan, Anhui Province, China. He received his Ph.D. degree from Changwon National University, Korea in 1999 and completed his post-doctor research at the Purdue University, IN, USA in 2001. He worked as a research associate at the Purdue University, Indiana USA from 2001-2002. Since 2002 he worked as a researcher at the Florida State University, Tallahassee, FL USA. His research interests include robotics, mobile robot, service robot, mechanical design and biomechanics. He is the PI of many projects on robotics supported by the Ministry of Science and Technology (MOST) of China and Anhui Provincial government etc., including bilateral and international cooperation projects between China and Germany, Serbia as well as other countries. He is also editors of several international journals on robotics. He has over 150 papers published in international journals and conference proceedings.

Prof. Daqi Zhu, University of Shanghai for Science and Technology, China
Daqi Zhu is a professor, doctoral supervisor, and Hu-Jiang distinguished professor of University of Shanghai for Science and Technology. He is also the director of the Department of Robotics Engineering and the dean of the Underwater Vehicle and Intelligent System Lab.. He mainly engaged in basic research and application development of Underwater Vehicles and intelligent system. He hosted more than 20 projects including the National Science and Technology Support Program, Two Key Projects of the National Natural Science Foundation of China, Five National Foundation General Project, the National key research and development program. He published more than 100 papers, and authorized more than 30 national invention patents. He is also Associate Editor of International Journal of Robotics and Automation、Intelligence & Robotics.

Assoc. Prof. Ye Ye, Anhui University of Technology, China
Ye Ye, associate professor, deputy director of the Robotics Departmentin Anhui University of Technology. Shemainly engagesin research on robotics and network games. Shehosted projects including one National Natural Science Foundation project, one Humanities and Social Science Youth Fund project of the Ministry of Education, one Key Project of the Provincial Excellent Youth Talent Fund of Universities, and oe Anhui Provincial Natural Science Foundation Key Project.She published more than 30 papersin important domestic and international journals. She also received one third prize for outstanding scientific research achievements in humanities and social sciences in higher education institutions, one third prize in natural sciences in Anhui Province, and one third prize in social sciences in Anhui Province.

Summary:
The problem of mobile robot path planning under a dynamic environment in mobile robot domain is hot and difficult. Its task is to find a path, which is from the initial state to goal state. Currently, common path planning methods are artificial potential field method, grid method, neural network method, chaos genetic algorithm, and so on. Artificial potential field method in the algorithm of path planning is relatively mature and efficient, because of the simplicity of the mathematical calculation, it is widely used. However, there are the issues of local minimum point and destination unreachable in traditional artificial potential field method. There are a variety of ways to escape from the local minimum point, such as random fleeing method, heuristic search, walking along the wall, Tangent bug’s method. These methods need to apply an additional control force to the robot, which could not fundamentally solve problems. 
Through the workshop, the researchers and experts in the field of motion planning of mobile robots are welcome to submit their research paper and come together to share their research results.

Keywords:
Motion Planning, trajectory planning, unmanned ground vehicles(UGV), mobile robot
11

Robotic Hand Design and Intelligent Control

Chairs:

Prof. Guanjun Bao, Zhejiang University of Technology, China
Guanjun Bao is a professor, doctoral supervisor, and chief professor of robotics engineering at Zhejiang University of Technology. He is also the director of the Institute of Mechanical and Electronic Engineering and the dean of the Guangdong Research Institute (Zhejiang University of Technology). He mainly engaged in basic research and application development of robots and intelligent equipment, as well as soft robotics and robotic hands. He hosted more than 20 projects including the National Science and Technology Support Program, the National Natural Science Foundation Shenzhen Robot Center Key Support Project, the National Foundation General Project, the National Foundation Youth Fund Project, the National Key R&D Plan Project, and the Zhejiang Provincial Key R&D Plan Project. He published more than 80 papers, 1 academic monograph, and authorized more than 40 national invention patents. He is also senior member of IEEE, member of the International Society of Biomimetic Engineering, senior member of the Chinese Society of Mechanical Engineering, and the second level of Zhejiang Province 151 Talent Project (Digital Economy Special Project).


Prof. Xiangrong XuAnhui University of Technology, China
Xiangrong Xu (Member, IEEE) currently is a professor in the School of Mechanical Engineering at the Anhui University of Technology, Ma'anshan, Anhui Province, China. He received his Ph.D. degree from Changwon National University, Korea in 1999 and completed his post-doctor research at the Purdue University, IN, USA in 2001. He worked as a research associate at the Purdue University, Indiana USA from 2001-2002. Since 2002 he worked as a researcher at the Florida State University, Tallahassee, FL USA. His research interests include robotics, mobile robot, service robot, mechanical design and biomechanics. He is the PI of many projects on robotics supported by the Ministry of Science and Technology (MOST) of China and Anhui Provincial government etc., including bilateral and international cooperation projects between China and Germany, Serbia as well as other countries. He is also editors of several international journals on robotics. He has over 150 papers published in international journals and conference proceedings.

Summary:
Artificial hand is one of the important parts for robots, especially for humanoid robot which is current the hot topics in both science community and engineering field. Although the design and study on robotic hand have always been interested and put into efforts, only simple structured hand (most are grippers) could be applied in engineering scenarios. That is, there are still problems and open challenges ahead to be investigated and solved. In this workshop, we are intending to discuss these issues, from the perspectives ranging from industry, home applications, to social requirements. In addition to the novel mechanism and structures, sensing is another important topic for robotic hand, which can provide the similar function of human skin to gather information during contacting and manipulation. Furthermore, the strategy of manipulation of the hands can learn the skills from their human counterparts. Finally, all the expected functions can only be realized when there is an intelligent controller to handle the hand. Thus, we would like to invite a wide range of talks in this workshop and discuss with each other with the expectation of arising new ideas and cooperation.

Keywords:
Robotic hand, control, smart sensing, manipulation, mechanism
12

Construction Robotics

Chairs:

Assoc. Prof. Shuai Fan, Chengdu University of Technology, China
Shuai Fan is currently an Associate Professor with School of Mechanical and Electrical Engineering, Chengdu University of Technology, China. He received the PhD degree in Mechanical Engineering (majoring in robotics) from University of Electronic Science and Technology of China, in 2020. His main research interests include robotics, automation design and intelligent optimization Methods. More than 40 Articles have been published on industrial robots, construction robots, and medical robots, with a total research funding of over 10 million.


Assoc. Prof. Chao LiChengdu University of Technology, China
Chao Li is currently an Associate Professor with School of Mechanical and Electrical Engineering, Chengdu University of Technology, China. He received the PhD degree in Mechanical Engineering (majoring in mechanicaldesignandtheory) from SichuanUniversity, in 2019. His main research interests include robotics,mechanism and machine theory.


Assoc. Prof. Kai WangChengdu University of Technology, China
Kai Wang is currently an Associate Professor with School of Mechanical and Electrical Engineering, Chengdu University of Technology, China. He received the PhD degree in Mechanical Engineering (majoring inmechanical engineering) fromSouthwest Petroleum University, in 2016. His main research interests include signal processing and fault detection and diagnosis,robotics.

Summary:
The main audience of the construction roboticsworkshop is builders and implementers of intelligent construction projects such as intelligent buildings, intelligent transportation, smart construction sites, smart buildings, smart cities, and smart fire protection. The main purpose is to promote the application of modern technological means in the construction process, including intelligent surveying and mapping, intelligent design, intelligent construction, and intelligent operation and maintenance management. It also includes the design, construction management, information technology services, and consulting services of construction projects, including intelligent planning and design, intelligent equipment and construction, intelligent facilities and disaster prevention, intelligent operation and maintenance and management of general civil engineering projects. Targeting future new BIM modeling technologies, prefabricated buildings, construction robots, full process engineering consulting, engineering general contracting and other engineering construction industries and models.

Keywords:
Intelligent buildings, Construction robot, Complex working conditions
13

Fault-Tolerant and Security Control for Cyber-Physical Systems

Chairs:

Prof. Jin-Liang Wang, Tiangong University, China
Jin-Liang Wang (Senior Member, IEEE) currently is a professor in the School of Computer Science and Technology, Tiangong University, Tianjin, China. His current research interestsinclude passivity, synchronization, cooperative control, complex networks,coupled neural networks, coupled reaction–diffusion neural networks, andmultiagent systems.Prof. Wang was a Managing Guest Editor for the Special Issue onDynamical Behaviors of Coupled Neural Networks With Reaction–DiffusionTerms: Analysis, Control, and Applications in Neurocomputing. He serves asan Associate Editor for the Neurocomputing and the International Journal ofAdaptive Control and Signal Processing.


Prof. KaiboShi, Chendu University, China
Kaibo Shi currently is a professor in the School of Information Science and Engineering,Chengdu University, Sichuan, China. His current research interests include robust control, sampled-datacontrol systems, and networked control systems.


Assoc. Prof. Zi-Peng Wang, Beijing University of Technology, China
Zi-Peng Wang (Senior Member, IEEE) currently is an associate professor in the Faculty of Information Technology,Beijing Laboratory of Smart Environmental Protection, and BeijingInstitute of Artificial Intelligence, Beijing University of Technology, Beijing, China. His current research interestsinclude robust control and filtering, fuzzy modeling and control, securecontrol, networked control systems, distributed parameter systems, and neuralnetworks.

Summary:
Cyber-physical systems (CPSs), which are an integration of computation, networking, and physical processes, play an increasingly important role in critical infrastructure, government and everyday life. Due to physical constraints, embedded computers and networks may give rise to some additional security vulnerabilities, which results in losses of enormous economy benefits or disorder of social life. Moreover, as the complexity of CPS increases, it becomes more and more challenging to ensure the reliability of CPS, especially in the presence of failures. As a result, it is of significant to investigate the security and reliability issue of CPSs to ensure that such systems are operating in a safe and reliable manner. This workshop presents some recent advances on fault-tolerant and security control for CPSs.

Keywords:
Fault-tolerant control; security control; cyber-physical systems
14

Computer Vision and Pattern Recognition

Chair:

Prof. Huimin Lu, Changchun University of Technology, China
Huimin Lu is a professor at Changchun University of Technology in China and serve as a Ph. D. supervisor in the field of Statistics and a Master's supervisor in Computer Science and Technology. She also is the associate dean at the School of Computer Science and Engineering at Changchun University of Technology. She serves as members of prestigious organizations such as ACM and IEEE, and held senior and lifelong memberships in the China Computer Federation. Within the China Computer Federation, she serves as a committee member for Artificial Intelligence and Pattern Recognition, Big Data, and Computer Vision. Her research interests encompass various areas, including Artificial Intelligence and Applications, Computer Vision, Biometric Recognition, and Intelligent Data Processing. She have served as the principal investigator for 13 research projects, including projects funded by the National Natural Science Foundation of China, the National Postdoctoral Science Foundation, and the Key Laboratory Projects of the Ministry of Education. She has published 12 SCI-indexed papers as the first author or corresponding author in renowned journals, including those listed in the first quartile of the Chinese Academy of Sciences' SCI index. As the leading contributor, she has received the Jilin Province Science and Technology Progress Third Prize and the National Business Federation Science and Technology Progress Third Prize. Furthermore, she has filed 12 invention patents as the first inventor (3 of which have been granted), obtained 11 utility model patents, and acquired 17 software copyrights.

Summary:
Computer vision and pattern recognition use computer technology, AI, and mathematical methods to carry out scientific research on the representation of image and video information, encoding and decoding, image segmentation, image quality evaluation, target detection and recognition and stereo vision. The main research contents include: pattern recognition and security monitoring of image and video, medical and material image processing, evolutionary algorithm, artificial intelligence, deep learning and data mining. It is widely used in Robotics, Artificial Intelligence and Control Science and Engineering.
The aim of this workshop is to bring together the research accomplishments of computer vision and pattern recognition provided by researchers from academia and the industry. The other goal is to show the latest research results in the field of computer vision and pattern recognition. We encourage prospective authors to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.

Keywords:
Computer vision, pattern recognition, deep learning, image processing, machine learning
15

Intelligent Control and Optimisation for Complex Systems

Chair:

Prof. Shiyuan Han, Unviersity of Jinan, China
Shi-Yuan Han received the M.S. and Ph.D. degrees in computer science and technology from the Ocean University of China, Qingdao, China, in 2009 and 2012, respectively. From 2011 to 2012, he had been a Visiting Scholar with the School of EECS, Queensland University of Technology, Brisbane, QLD, Australia. In 2012, he joined the University of Jinan, Jinan, China, where he is currently a Professor with the Shandong Provincial Key Laboratory of Network Based Intelligent Computing. From 2021 to 2022, he had been a Visiting Scholar with the David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada. His current research interests include the areas of fault tolerant control, vibration control, intelligent transportation systems, time-delay systems, evolutionary computation, networked control systems, and their applications in intelligent transporation systems.

Summary:
Intelligent control and optimisation at the interface between AI/Machine learning and the fields of control and optimisation. They encompass methodologies such as neural network-based control, fuzzy control, evolutionary and nature inspired learning and optimisation, and reinforcement learning. As technology continues to advance and we seek to address global challenges around economic, environmental, and social sustainability, the need for intelligent control approaches that can optimally operate complex processes and systems becomes increasingly crucial. However, many challenges limit their wide-scale adoption, from dealing with data quality and volume issues to achieving scalable robust, understandable and safe solutions. This special issue aims to address these challenges and/or showcase the latest real-world applications and enabling algorithmic advances in Intelligent Control and Optimisation for complex systems, such as intelligent perception, intelligent control, and optimal control for complex systems.

Keywords:
intelligent perception, intelligent control, and optimal control for complex system