Innovative Magnetorheological Devices and Applications
Thursday, June 29th
10:00 AM -12:00 PM
Organizers:Yancheng Li, University of Technology Sydney (Australia), Haiping Du, University of Wollongong (Australia)
The invited session will bring researchers together to share recent advances in applications of magnetorheological (MR) materials in vibration control, vehicle dynamics and related areas. In this session, six invited papers will be presented, covering magnetorheological device development, theoretical and experimental studies on semi-active suspension and haptic devices. This session will cover various applications of magnetorheological materials, including development of semi-active vehicle suspension, new MR device development for haptic apparatus, innovative device for multiple mode vibration isolation, etc. All above research and development represent leading research in the field which underpins the great potential of the MR materials.
Damage Detection, Diagnosis and Prognosis of Materials and Structures Using Artificial Intelligence
Thursday, June 29th,
15:00 PM -17:00 PM
Organizers:Jing Rao, The University of New South Wales (Australia), Yaguo Lei, Xi'an Jiaotong University (China), Sattar Dorafshan, University of North Dakota (USA)
Damage detection, diagnosis and prognosis of materials and structures play an important role in structural health monitoring (SHM), and condition assessment. The typical components of an SHM system include sensor selection and placement, data acquisition, data transmission, data processing and control, data management, structural health evaluation, decision-making, and inspection and maintenance. Sensing technologies (data acquisition and data transmission) and data processing algorithms are two critical factors for the success of SHM of materials and structures. Damage diagnosis using artificial intelligence algorithms can provide important information for assessing current conditions and predicting the future performance of materials and structures. Damage prognosis methods and performance assessment techniques can ensure the safe operation of structures and help determine cost effective maintenance strategies. The objective of the invited session is to share and discuss recent advances in the development and application of artificial intelligence for damage detection, diagnosis and prognosis of materials and structures. Topics covered in this invited session include, but are not limited to, the latest ideas and advances in theories, techniques, and methods used to advance knowledge in different aspects of artificial intelligence, such as smart sensors, data mining and processing, structural damage diagnosis and prognosis, and artificial intelligence algorithms, as well as case studies that demonstrate the practical application of advanced artificial intelligence techniques.
Intelligent Human-Machine Collaboration for Advanced Mechatronics and Robotics
Thursday, June 29th
15:00 PM -17:00 PM
Organizers:Chen Lv, Nanyang Technological University (Singapore), Yifan Wang, Nanyang Technological University (Singapore), Yang Xing, Cranfield University (UK), Huang Chao, The Hong Kong Polytechnic Univeristy (China)
Before realizing full autonomy, human-machine collaboration with multi-modal human-machine interface (HMI) will play a significant role in the development of advanced robotics, mechatronics, and machine intelligence. Multi-modal HMI consists of a class of artificial interfaces that connect a person to a machine, system, or device. They can record varying human inputs and provides feedback through tactile, visual, auditory, olfactory, and gustatory signals, and enables safe, smart and smooth human-machine interactions and collaboration. As the cornerstone of HMI, a broad range of sensors have been developed to monitor mechanical (e.g., strain, pressure, torque), biological (e.g., electrophysiology and metabolic biomarkers), and other input signals. In the past decades, this field has gained remarkable progress due to the advances in soft materials, intelligent structures, flexible electronics as well as data-driven machine learning technologies, which may support and lead to a new era of smart robotics. In the meantime, however, new challenges, for example how to ensure a safe, intelligent, and comfortable interactions and collaboration between humans and automation functionalities, remain opening. In this context, novel human-machine interfaces are expected to be designed and developed to make full use of the great potentials and advantages of both humans and automation systems. Therefore, novel interface design, efficient interaction and collaboration approaches between human and machine for increasing the mutual understanding, trust, and bilateral acceptance are of great importance for the development of advanced robotics and mechatronics. This special session aims to provide up-to-date research concepts, and practical solutions that could help advance the human-machine collaboration for advanced mechatronics and robotics.