Special/Invited Sessions

Special Session
Biologically Inspired Intelligence for Mechatronics and Robotics

Description: Biologically inspired intelligence technique, an important embranchment of series on computational intelligence, plays a crucial role for robotics. The autonomous robot and vehicle industry has had an immense impact on our economy and society, and this trend will continue with biologically inspired intelligence techniques. Biologically inspired intelligence, such as biologically inspired neural networks (BINN), is about learning from nature, which can be applied to the real-world robot and vehicle systems. Recently, the research and development of bio-inspired systems for robotic applications is increasingly expanding worldwide. Biologically inspired algorithms contain emerging sub-topics such as bio-inspired neural network algorithms, brain-inspired neural networks, swam intelligence with BINN, ant colony optimization algorithms (ACO) with BINN, bee colony optimization algorithms (BCO), particle swarm optimization with BINN, immune systems with BINN, and biologically inspired evolutionary optimization and algorithms, etc. Additionally, it is decomposed of computational aspects of bio-inspired systems such as machine vision, pattern recognition for robot and vehicle systems, motion control, motion planning, movement control, sensor-motor coordination, and learning in biological systems for robot and vehicle systems.

This special session seeks to highlight and present the growing interests in emerging research, development and applications in the dynamic and exciting areas of biologically inspired algorithms for mechatronics and robotics and vehicle systems (autonomous robots, unmanned underwater vehicles, and unmanned aerial vehicles).

Invited Session
Innovative Magnetorheological Devices and Applications

Description: 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.

Invited Session
Damage Detection, Diagnosis and Prognosis of Materials and Structures Using Artificial Intelligence

Description: 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.

Invited Session
Intelligent Human-Machine Collaboration for Advanced Mechatronics and Robotics

Description: 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.