Name: Prof. Chaoquan Tang
Affiliation: China University of Mining and Technology, China
Biography: Chaoquan Tang, PhD. , Prof. of China University of Mining and Technology, head of the department of robot engineering in the School of Mechanical and Electrical Engineering, China University of Mining and Technology, and deputy director of the Key Laboratory of Mine Mechanical and Electrical Equipment in Jiangsu Province. Presided over 2 National Natural Science Foundations; One key R&D project in Jiangsu Province, one natural science fund in Jiangsu Province, one project supported by Dr. China, one project participated in the 863 project, and two national key R&D projects. The first author/correspondent published more than 20 SCI papers, and authorized more than 20 national invention patents. He is currently a member of the Committee of Cognitive System and Information Processing of China Artificial Intelligence Society, the Committee of Construction Robot of China Automation Society and the Committee of China computer federation Intelligent Robot. Research interests: design of special robots in narrow spaces, unmanned construction machinery, UAV control, SLAM, reinforcement learning, etc.
Speech Title: Autonomous Positioning and Navigation Technology of Mining Robots
Abstract: The autonomous positioning and navigation technology of mining robots is a key support for realizing intelligent and unmanned mining operations. With the increase in the depth of mineral resource extraction and the complexity of the working environment, traditional manual mining is faced with problems such as high safety risks and low efficiency. Mining robots can effectively address challenges such as the absence of satellite positioning signals underground and obstacle avoidance of dynamic obstacles through autonomous positioning and navigation technologies. This report focuses on the research of technologies such as laser SLAM, UWB (Ultra-Wideband) positioning, and multi-sensor fusion, as well as their applications in scenarios such as mining, gas extraction, and inspection. These technologies can effectively improve mining efficiency and reduce the incidence of safety accidents.
Name: Assoc. Prof. Xian Guo
Affiliation: Nankai University, China
Biography: Xian Guo received the B.S. degree in mechanical design, manufacturing, and automation from the Huazhong University of Science and Technology, Wuhan, China, in 2009, and the Ph.D. degree in mechatronics from the Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China, in 2016. From 2016 to 2018, he was a Postdoctoral Fellow with Nankai University, Tianjin, China, where he is currently an Associate Professor with the Institute of Robotics and Automatic Information Systems. In recent years, he has combined artificial intelligence algorithms with the motion control of bionic robots to explore the application of deep reinforcement learning in the motion control of bionic robots. At the same time, he has actively applied the deep reinforcement learning to robot game. At present, he has published more than 40 papers in important academic journals and conferences.
Speech Title: Learning-Based Motion Control for Snake Robots
Abstract: Snake robots are composed of multiple modules in series, which can generate many gaits, therefore, they have a strong ability to adapt to a variety of environments. This presentation introduces three motion control tasks for snake robots based on deep reinforcement learning: (1) a deep reinforcement learning-based arbitrary path tracking algorithm for 2D snake robots; (2) a representation reinforcement learning-based dense control method for 3D snake robots, designed for state-sparse perception; (3) a delay reinforcement learning-based dynamic winding motion control approach. Finally, future research directions are discussed.
Name: Assoc. Prof. Tongshuai Sun
Affiliation: Tianjin University, China
Biography: Associate Professor Tongshuai Sun, Mechanical Engineering School, Tianjin University, China. He has been engaged in research on innovative design methods and performance analysis of underwater vehicles, as well as smooth control methods for bionic multi-configuration underwater vehicles. He has published 30 high-quality papers in journals such as IEEE/ASME TMECH, SCI CHINA TECH SCI, and OCEAN ENG. As project leader, he is responsible for the following projects:National Youth Science Foundation (Class C), the National Defense Innovation Zone Project, a sub-project under the National Key Research and Development Program, the 17th China Postdoctoral Science Foundation Special Support Project, and the Tianjin Municipal Postdoctoral Innovation Position Support Projects. Together with team members, he received the 2022 11th China Technology Market Association “Golden Bridge Award” (8/10) and the 2020 Leaderobot China Robot Application Innovation Award (8/10).
Speech Title:Design and Application of Controllable Bionic Attachment Mechanisms for Underwater Gliders
Abstract: Underwater gliders (UG) are an important platform for realizing continuous three-dimensional marine observation, which are playing a more and more prominent role in ocean economy, marine science and technology, and marine security. The flow field, hydrography, topography and other ocean conditions show obvious temporal and spatial variability, which puts forward new requirements for UGs, such as adaptability to the marine environment, deformation of the shape, and switch between navigation modes. To break through the performance bottleneck of traditional UGs with insufficient environmental adaptability, limited observation and detection capability, and weak motion maneuverability, this report proposes a design method for controllable bionic attachment mechanisms of UGs by taking the screw theory as the mathematical description and configuration tool and integrating the design concept of multi-motion fusion. Then, based on the kinematic constraint that UG attachments are similar to marine organisms with the ability of self-repair, self-expansion, self-reconfiguration and other "on-demand adjustments", this report proposes a variety of controllable bionic attachment mechanisms with engineering applications, and successfully develops a variety of novel UGs with the abilities to control the bow/tail attitude, regulate the parameters of the wing, adjust the spatial state of the wing, and regulate the wing/tail motion frequency, etc. Furthermore, this research provides a referential configuration method and theoretical guidance for the innovative design of multi-mode, multi-drive and multi-function hybrid-driven unmanned underwater vehicles.
Name: Assoc. Prof. Liangming Chen
Affiliation: Southern University of Science and Technology, China
Biography: Liangming Chen joined Southern University of Science and Technology in December 2022 as an associate professor. Before joining SUSTech, he worked as a postdoctoral researcher in the research group of Professor Xie Lihua (Fellow of the Singapore Academy of Engineering, IEEE Fellow) at Nanyang Technological University, Singapore. He and his collaborators developed the theory of angle rigidity theory and applied it to multi-agent formation control and distributed localization. As the first author, he published multiple research results in top journals in the field of control and robotics, including IEEE TAC, Automatica, IEEE TRO, IJRR, etc. He is an associate editor of the IEEE Transactions on Robotics, and IEEE Transactions on Systems, Man, and Cybernetics: Systems. He is a senior member of IEEE, and has been selected for the National High-level Talent Program Youth Project and Shenzhen Overseas High-level Talent Program.
Speech Title: Multi-Robot Cooperative Localization and Swarm Formations Based on Angle Rigidity Theory
Abstract: In recent years, there has been an increasing demand for unmanned system (or intelligent system) swarm formations in the fields of sea, land, air, and space, which have important application value in tasks such as ocean monitoring, ground exploration, aerial operations, and deep space exploration. However, in many environments (such as buildings, tunnels, forests, underwater, and denied environments), the global positioning system (GPS) is unreliable or non-existent, which requires research on how to perform collaborative localization and formation control based on local measurement information between unmanned systems. This talk will introduce the collaborative localization and formation control of unmanned systems in GPS-denied, communication-degraded, or denied environments, as well as a mathematical tool developed to solve these engineering problems: angle rigidity theory.