Special Session VIII

Perception and Control of Robots in Human-Robot Shared Environments

Submission Guideline:

Please submit your manuscript via Online Submission System: https://easychair.org/conferences/?conf=rcae2024
Please choose Special Session: Perception and Control of Robots in Human-Robot Shared Environments

Introduction:

The integration of robots into environments shared with humans represents one of the most transformative developments in modern technology. This integration encompasses various applications such as collaborative manufacturing, service robotics in healthcare and domestic settings, autonomous driving, and smart urban environments. As robots become increasingly prevalent in spaces traditionally occupied by humans, the need for sophisticated perception and control systems grows significantly. This special session focuses on the latest advancements, challenges, and opportunities in the perception and control of robots operating in human-robot shared environments.
The dynamic and often unpredictable nature of human-populated environments poses significant challenges for robotic systems. Unlike controlled industrial settings, human-robot shared environments require robots to adapt to a wide range of variables, including human behaviors, complex and cluttered spaces, and dynamic changes in the environment. To address these challenges, robust perception systems and advanced control algorithms are essential. Robotic perception involves the acquisition and interpretation of sensory information to understand and interact with the environment. This includes the use of cameras, LiDAR, radar, and other sensors to create a comprehensive model of the surroundings. In human-robot shared environments, perception systems must be capable of recognizing and predicting human actions, understanding intent, and distinguishing between various objects and obstacles. Control systems, on the other hand, involve the decision-making processes that enable robots to perform tasks efficiently and safely. These systems must integrate perceptual data to navigate, manipulate objects, and interact with humans in a seamless manner. Advanced control algorithms often employ techniques from artificial intelligence, machine learning, and robotics to achieve high levels of autonomy and adaptability.

Session Themes
This special session seeks contributions from researchers, practitioners, and industry experts to discuss the themes including but not limited to the following aspects:

  1. Advanced Sensor Technologies and Integration:
    1. Development and integration of novel sensors for enhanced perception in human-robot shared environments.
    2. Multi-sensor fusion techniques to improve robustness and accuracy in complex environments.
    3. Real-time processing of sensory data for dynamic decision-making.
  2. Machine Learning and Artificial Intelligence in Robotic Perception:
    1. Application of machine learning algorithms for object recognition, human detection, and activity prediction.
    2. Deep learning techniques for improving the perceptual capabilities of robots.
    3. AI-driven approaches for semantic understanding of human-robot shared spaces.
  3. Human-Robot Interaction (HRI) and Social Robotics:
    1. Design and evaluation of intuitive human-robot interfaces.
    2. Techniques for effective communication and collaboration between humans and robots.
    3. Studies on human factors and ergonomics in shared environments.
  4. Autonomous Navigation and Path Planning:
    1. Algorithms for safe and efficient navigation in dynamic and populated environments.
    2. Path planning techniques that consider human presence and movements.
    3. Strategies for obstacle avoidance and environment mapping.
  5. Safety and Reliability in Human-Robot Shared Spaces:
    1. Risk assessment and mitigation strategies for safe robot operation.
    2. Redundancy and fault-tolerant control systems.
    3. Standards and regulations for robots in shared environments.
  6. Robotic Manipulation and Object Handling:
    1. Techniques for dexterous manipulation in cluttered and dynamic settings.
    2. Grasp planning and object recognition in the presence of humans.
    3. Collaborative manipulation tasks involving human-robot teams.
  7. Ethical and Societal Implications:
    1. Ethical considerations in the deployment of robots in human environments.
    2. Societal impacts and acceptance of robots in everyday life.
    3. Policy and governance frameworks for human-robot coexistence.
  8. Case Studies and Real-World Applications:
    1. Success stories and lessons learned from deploying robots in human-robot shared environments.
    2. Cross-disciplinary projects and collaborations.
    3. Demonstrations of innovative applications in sectors such as healthcare, manufacturing, transportation, and domestic services.

Organizers:


Fan Xu, Assistant Professor

Shanghai Jiao Tong University, China

Fan Xu received a B.Eng. degree in New Energy Science and Engineering from Huazhong University of Science and Technology, China, in 2015, an M.S. degree in Mechanical Engineering from Arizona State University, USA, in 2016, and a Ph.D. degree in Control Science and Engineering from Shanghai Jiao Tong University, China, in 2021. She was a Post-Doctoral Fellow with the Department of Automation at Shanghai Jiao Tong University from 2021 to 2023. She is currently an assistant professor at the Department of Automation, Shanghai Jiao Tong University, Shanghai, China. Her research interests include soft robots and visual servoing.


Yixuan Sheng, Assistant Professor

Harbin Institute of Technology, Shenzhen, China

Yixuan Sheng, Ph.D., Harbin Institute of Technology, Shenzhen, P.R. China, assistant professor. Her research interests focus on multimodal wearable sensing technology, biosignal processing and neurorehabilitation. She proposed the quantitative evaluation methods for motor function based on muscle synergy and corticomusclar coherence, applied to motor disorders.


Xiangyu Chu, Postdoctoral Fellow

The Chinese University of Hong Kong, China

Xiangyu Chu received the B.Eng. degree in automation, the M.Eng. degree in control science and engineering from the Harbin Institute of Technology, Harbin, China, in 2015 and 2017, respectively, and the Ph.D. degree in mechanical and automation engineering from The Chinese University of Hong Kong, Hong Kong, China, in 2021. He was a Visiting Student with Carnegie Mellon University, Pittsburgh, PA, USA, in 2020. Besides, he was visiting the Chair for Computer Aided Medical Procedures & Augmented Reality (CAMP) at Technical University of Munich, Germany, from July 2023 to Jan 2024. He is currently a Postdoctoral Fellow with the Multi-Scale Medical Robotics Center, Hong Kong, and also an Honorary Postdoctoral Fellow with the Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong. His research interests are developments of robotic surgical and medical systems and related algorithms, developments of nuanced manipulation skills on (deformable) objects and their applications in surgery and service, and developments of agile locomotion systems and related algorithms / their applications on biomechanics.