熊凌，女，博士，教授，美国华盛顿州立大学访问学者。毕业于华中科技大学图像识别与人工智能研究所，获工学博生学位。主要研究领域：模式识别与智能系统、图像处理及其应用等。主持完成国家自然科学基金1项，参加国家自然科学基金项目4项，主持湖北省自然科学基金1项、湖北省技术创新专项重点项目2项、湖北省重点研发项目1项。获湖北省科技进步二等奖2项、湖北省技术发明三等奖1项、中国机械工业科学技术进步二等奖1项；获授权发明专利和实用新型专利10余项、软件著作权3项；发表学术论文50余篇。主编或副主编教材5部，获国家级教学成果二等奖1项、省级教学成果二等奖1项。

    Xiong Ling, female, PhD, professor, visiting scholar at Washington State University in the United States. Graduated from the Institute of Image Recognition and Artificial Intelligence at Huazhong University of Science and Technology with a PhD degree in Engineering. Main research areas: pattern recognition and intelligent systems, image processing and its applications, etc. Led the completion of one National Natural Science Foundation of China, participated in four National Natural Science Foundation of China, and led one Hubei Provincial Natural Science Foundation project, two Hubei Provincial Key Projects for Technological Innovation, and one Hubei Provincial Key R&D project. Received 2 second prizes for scientific and technological progress in Hubei Province, 1 third prize for technological invention in Hubei Province, and 1 second prize for scientific and technological progress in China's machinery industry; More than 10 authorized invention patents and utility model patents, as well as 3 software copyrights; Published over 50 academic papers. Editor in chief or deputy editor in chief of 5 textbooks, awarded 1 second prize for national teaching achievements and 1 second prize for provincial teaching achievements.

    程磊，男，博士，教授，英国西英格兰大学联合博士生导师。入选“湖北省新世纪高层次人才工程”计划，第九届武汉市“洪山地区十大优秀青年”。长期从事机器人与智能嗅视感知等方面的研究与教学工作。兼任中国人工智能学会青年工作委员会常务委员、中国人工智能学会智能机器人专业委员会常务委员、湖北省自动化学会理事、湖北省人工智能学会理事、武汉市自动化学会常务理事。主持及参与国家自然科学基金6项，主持省部级科教研项目9项，发表论文60余篇，获国际国内学术奖励10项、学生竞赛国家奖20余项。

    Cheng Lei, male, PhD, professor, joint doctoral supervisor at the University of West England in the United Kingdom. Selected as one of the "Hubei Province New Century High level Talent Project" and one of the "Top Ten Outstanding Youth in Hongshan Region" in the 9th Wuhan City. Engaged in research and teaching in robotics and intelligent olfactory perception for a long time. He also serves as an executive member of the Youth Work Committee of the Chinese Artificial Intelligence Society, an executive member of the Intelligent Robot Professional Committee of the Chinese Artificial Intelligence Society, a director of the Hubei Provincial Automation Society, a director of the Hubei Provincial Artificial Intelligence Society, and an executive director of the Wuhan Automation Society. Hosted and participated in 6 projects funded by the National Natural Science Foundation of China, 9 provincial and ministerial level scientific and educational research projects, published over 60 papers, and won 10 international and domestic academic awards, as well as more than 20 national awards in student competitions.

    陈洋，男，教授，博士生导师。2012年毕业于中国科学院沈阳自动化研究所机器人学国家重点实验室，获博士学位，2005年和2002年分别毕业于中南大学获得硕士和学士学位。现为湖北省自动化学会理事，湖北省人工智能学会理事，中国自动化学会机器人竞赛工作委员会委员。主要研究领域为移动机器人建模、规划与控制。主持国家自然科学基金项目3项、国家重点研发计划专项子课题1项、辽宁省科技厅联合基金1项、湖北省教育厅科研课题1项。发表学术论文50多篇，发明专利10项（包括美国发明专利1项、欧洲发明专利1项），实用新型专利2项，软件著作权登记6项。获得省级教学成果二等奖1项，被评为首届武汉科技大学优秀研究生导师。

    Dr. Chen Yang is currently a professor at the School of Information Science and Engineering, Wuhan University of Science and Technology. He got his PhD from the State Key Laboratory of Robotics at the Shenyang Institute of Automation, Chinese Academy of Sciences. His research focuses on the modeling, planning, and control of mobile robots. Currently, his main research is on multi-robot collaborative path planning for applications such as continuous monitoring, emergency rescue, agricultural spraying, building inspection, and road patrols. The decision-making of robots faces challenges from various uncertainties, including unreliable communication quality between robots, road network congestion, obstacles, battery levels, adverse weather conditions, electronic and mechanical failures, among others. Therefore, optimal decision-making for robots should possess certain resilient features such as robustness, redundancy, fault tolerance, and flexibility.