Invited Sessions

Session Name Organizers
Advanced Battery Management and Control in Autonomous Mobile Robots Guangzhong Dong
Yujie Wang
Zhongbao Wei
Weiji Han
Bioinspired Mechatronics of Intelligent Unmanned Systems Wei He
Zhijun Li
Gianluca Antonelli
Okyay Kaynak
Toshio Fukuda
Underwater Robotic Systems Lei Cai
Zhenxue Chen
Lan Wu
Open Challenges and State-of-the-Art in Advanced Control of Medical Robot Applications Hang Su
Jing Guo
Bo Xiao
Yue Chen
Elena De Momi
Human-Machine Systems for Automated Driving Chao Huang
Yahui Liu
Xiaoxiang Na
Chen Lv

Advanced Battery Management and Control in Autonomous Mobile Robots

Mobile robots are emerging as the backbone of numerous industrial and civilian systems where human intervention is deemed risky. Their performance and reliability rely heavily on the battery management and control. Inaccurate modeling and estimation of battery behaviors may result in inappropriate battery operation, such as premature battery failures and degradation. These factors may in turn lead to immobilization of the robot during the mission. In recent decades, advanced battery management and control has attracted considerable attention from various communities. However, battery management in mobile robots has not drawn sufficient attentions and is typically addressed by setting simple battery operating thresholds. Consequently, no risk evaluation of the battery depletion has been considered during the charge scheduling. This invited session aims at attracting researchers and engineers whose scientific interests reside in the management and control of lithium-ion batteries, with special application in autonomous mobile robots. The main objective is to provide timely solutions and technical merits for the management and control of batteries in mobile robots.

Topics of interest will be focused on, but not limited to:

  • Modeling, estimation, control, and optimization for lithium-ion batteries;
  • Evaluation and prediction of risks of battery depletion for mobile robots;
  • Battery health/ageing modeling, diagnosis and prognostics;
  • Battery charge scheduling in autonomous mobile robots;
  • Optimal, fast, health-aware charging, balancing control, etc;
  • Failure detection and fault tolerance control in battery management;
  • Application of machine learning and artificial intelligence on battery management and control issues;

This invited session is sponsored by the IEEE International Conference on Advanced Robotics and Mechatronics (ICARM), 2020.



Bioinspired Mechatronics of Intelligent Unmanned Systems

With the recent growth in the application areas of unmanned systems, we are faced with a need for mechatronic systems that are capable of accomplishing complicated missions. On the other hand, the design and implementation of bioinspired mechatronic systems is one of the most challenging tasks in unmanned systems since they often have to operate under diverse and difficult environmental conditions. The subject has therefore received increasing attention in recent years, due to the growing demands both from industry and military. For this reason, the conception, the development and the implementation of mechatronic systems with higher levels of intelligence than of todays have become urgent issues.

Topics explored in this focused section will include, but are not limited to:

  • Bioinspired mechatronics systems for intelligent unmanned systems
  • Precise positioning/tracking control of intelligent unmanned systems
  • Mechatronic system design and implementations for intelligent unmanned systems
  • Sensing and control systems for intelligent unmanned systems
  • Optimizations for intelligent unmanned systems
  • Intelligent unmanned systems in social applications
  • Intelligent unmanned systems in healthcare
  • Intelligent unmanned systems in industrial applications
  • Intelligent unmanned systems in military
  • Modeling and identification for intelligent unmanned systems
  • New applications of bioinspired mechatronics in intelligent unmanned systems

Guest Editors


Target imaging and reinforcement under complex scenes for robotic systems

This Special Collection mainly focuses on target imaging under complex scenes and reinforcement via deep learning for robotic systems, addressing both original algorithmic development and new applications of target imaging under complex scenes. This Special Collection invites original papers presenting innovative ideas and concepts, new discoveries and improvements, and novel applications in the selected topics.

Guest Editors


Robotic technologies have revolutionized medical applications over the past few decades by introducing robotic systems in various medical procedures. However, the deployment and integration of robots in the medical operation has been hampered by issues such as limited sensory perception, safety concerns, and situational awareness for the human user, and having to operate in an unconstructed environment like in operation room or house living room. The development and design of novel control strategies are required to solve these challenges. By linking the clinical requirements considered with the capabilities of state-of-the-art robotic technologies, this invited session aims to bring together researchers, industry engineers, and scientists of different backgrounds and provide an opportunity to discuss solutions for designing control strategies and control software implementation for medical robot applications.

Open Challenges and State-of-the-Art in Advanced Control of Medical Robot Applications

Topics explored in this focused section will include, but are not limited to:

  • Evaluation methods and new methodologies for medical robot applications
  • Image-guided control and visual processing for medical system
  • Dynamics models and dynamics based controller design for medical robots
  • Stability, disturbance rejection, and robustness in clinical applications
  • Cooperative or semi-autonomous control of medical robots
  • Motion planning for surgical operative procedures
  • Social, ethical and aesthetic issues in the medical applications
  • Advanced biomedical signal processing
  • Human-computer interaction for biomedical applications
  • Device-free localization in medical application 
  • Robot-assisted rehabilitation/surgery robotics and diagnostics
  • Multi-modal based bio-signal processing and pattern recognition
  • Sensor-fusion in biomedical systems
  • Intelligent wearable and assistive medical devices
  • Advanced control algorithm for medical robot control


Human-Machine Systems for Automated Driving

Technical Outline of the Session and Topics:

Before realizing fully autonomous driving, highly automated vehicles will play a significant role in the development of vehicle intelligence technologies. Highly automated driving presents an exciting new development in vehicle technology, however, in the meantime it poses a new challenge, namely how to ensure a safe, smart, and smooth interactions between human driver and automation functionality. Therefore, a better understanding of the interaction between human driver and automation system becomes a key issue to the realization of effective and efficient driver-automation collaboration for automated driving.

The special session aims to provide up-to date research concepts, theoretical findings and practical solutions that could help implement the interactions between human and automation for connected automated vehicles.

Topics of interest include, but are not limited to:

  • Human interaction with vehicle automation
  • Human acceptability of, preference for, and adaption to vehicle automation
  • Human-automation shared control
  • Advanced Driver Assistance Systems (ADAS)
  • Human-machine interface and modalities for automated vehicles
  • Human cognitive and actuation behaviors
  • Decision making, path planning and control for autonomous vehicles
  • Vision, localization and navigation technologies for autonomous vehicles
  • Connected Automated Vehicle (CAV) technologies