Human Factors and Human-in-the-Loop; Human-Centered Automation; Human-Centered Robotics; Learning and Adaptive Systems; Learning from Demonstration; Physically Assistive Devices; Rehabilitation Robotics; Robust/Adaptive Control of Robotic Systems
Primary Areas: Aerial robotics, bioinspired flight, path planning for multiple mobile robots or agents, distributed robot systems, swarms, optimization and optimal control Secondary Areas: Space robotics, robust/adaptive control of robotic systems, autonomous vehicle navigation, SLAM
Adaptive Control; Aerial Robotics; Autonomous Agents; Collision Avoidance; Collision Detection and Avoidance; Computer Vision; Computer Vision for Robotics and Automation; Deep Learning in Robotics and Automation; Distributed Robot Systems; Dynamics; Mapping; Mobile Robots; Motion Control; Motion Control of Manipulators; Motion and Path Planning; Motion and Trajectory Generation; Multi-Robot Systems; Network Robotics; Networked Robots; Object Detection, Segmentation and Categorization; Optimization; Path Planning for Multiple Mobile Robots or Agents; Pose Estimation; Probability and Statistical Methods; RGB-D Perception; Robust/Adaptive Control of Robotic Systems; SLAM; Semantic Scene Understanding; Surveillance Systems; Visual Search; Visual Servoing; Visual Tracking; Visual-Based Navigation; Wheeled Robots
Primary Areas: Motion and path planning, manipulation planning, climbing robots Secondary Areas: 3D robot simulation and mathematical modeling of robots, humanoid robots, optimization and optimal control
AI-Based Methods; Agent-Based Systems; Autonomous Agents; Big Data in Robotics and Automation; Cognitive Human-Robot Interaction; Control; Deep Learning in Robotics and Automation; Dual Arm Manipulation; Human Factors and Human-in-the-Loop; Human-Centered Robotics; Imitation Learning; Learning Control; Learning and Adaptive Systems; Learning from Demonstration; Learning from/by Demonstration; Machine Learning; Model Learning for Control; Motion Control; Motor Primitives; Motor Skill Learning; Neural and Fuzzy Control; Physical Human-Robot Interaction; Probability and Statistical Methods; Reactive and Sensor-Based Planning; Robot Learning; Robot Reinforcement Learning; Robotics; Skill Acquisition and Learning
Computer Vision for Automation; Control Architectures and Programming; Deep Learning in Robotics and Automation; Domestic Robots; Force Control; Force and Tactile Sensing; Grasping; Humanoid Robots; Mobile Manipulation; Object Detection, Segmentation and Categorization; Perception for Grasping and Manipulation; Software, Middleware and Programming Environments
AI-Based Methods; Autonomous Agents; Cognitive Human-Robot Interaction; Deep Learning in Robotics and Automation; Human-Centered Robotics; Learning and Adaptive Systems; Learning from Demonstration; Physical Human-Robot Interaction; Social Human-Robot Interaction; Visual Learning
Primary; Computational Geometry; Reactive and Sensor-Based Planning; Planning, Scheduling and Coordination; Path Planning for Multiple Mobile Robots or Agents; Secondary; Task Planning; Formal Methods in Robotics and Automation; Motion and Path Planning; Networked Robots
Affective Computing; Biometrics; Cognitive Human-Robot Interaction; Computer Vision for Other Robotic Applications; Cooperating Robots; Cooperation and Collaboration in Human-Robot Teams; Deep Learning in Robotics and Automation; Detecting and Understanding Human Activity; Ethics and Philosophy; Gesture, Posture and Facial Expressions; Gesture, Posture, Social Spaces and Facial Expressions; Health Care Management; Human Centered Robotics; Human Factors and Human-in-the-Loop; Human detection & tracking; Human detection and tracking; Human robot interaction; Human-Centered Robotics; Human-Robot Interaction; Medical Robots and Systems; Non-verbal Cues and Expressiveness; Novel Interfaces and Interaction Modalities; Object Detection, Segmentation and Categorization; Object detection, segmentation, categorization; Performance Evaluation and Benchmarking; Personal Robots; RGB-D Perception; Robot Companions; Robot Companions and Social Human-Robot Interaction; Robot Companions and Social Robots in Home Environments; Robots in Education; Security Protocols; Semantic Scene Understanding; Service Robots; Social Human-Robot Interaction; Social Intelligence for Robots; Social robotics; Telerobotics; Therapy and Rehabilitation; User-centered Design of Robots; Visual Place Recognition
Dr. Yajing Shen received the PhD degree in 2012 from Fukuda Lab., Nagoya University, Japan, and he is working as Assistant Professor in Mechanical and Biomedical Engineering Department in City University of Hong Kong currently. His mainly research interest is micro/nanorobotics, including the micro/nano robots development and their applications in the fundamental and practical problems in biomedical, material, and other emerging fields. He has published ~100 papers in international journal/conference, and received serval awards, including the Best Manipulation Paper Award in IEEE International Conference on Robotics and Automation (ICRA) in 2011, the IEEE Robotics and Automation Society Japan Chapter Young Award in 2011, the Early Career Awards of Hong Kong UGC in 2014, Big-on-Small Award at MARSS 2018. He is a Senior Member of IEEE and an Executive member of China Micro-nano Robotic Society, and is very active in promoting micro/nano robotics to society, such as by serving as the committee member of international conference, organizing “micro/nano robot” workshop, special issue, and so on.
Talk # 1
Micro-Nano Robotic Systems in Biomedical Applications
Robotics have played important roles in biomedical applications owing to its advantages in precision, stability, dexterity and productivity. With the rapid development of micro-nano technology, the micro-nano robotic systems have received increasing attentions in recent years, which can be classified to two different categories according to their working principles and functions: (1) the robots can operate object with micro-nano scale resolution. (2) the robot is of micro-nano scale size. This talk will give two specific examples to demonstrate the above two types of robotic system in biomedical applications, i.e., one is the robot-aided high precision nano characterization system, and the other is the bio-inspired miniature robots. Lastly, the prospects of the micro-nano robotic systems will be discussed.
Assembly; Autonomous Agents; Dexterous Manipulation; Field Robots; Human-Centered Robotics; Hybrid Logical/Dynamical Planning and Verification; Intelligent and Flexible Manufacturing; Learning and Adaptive Systems; Learning from Demonstration; Micro-Data Policy Search; Mobile Manipulation; Model Learning for Control; Motion Control; Motion and Trajectory Generation; Motor Skill Learning; Perception for Grasping and Manipulation; Physical Human-Robot Interaction; Programming Environment; Robot Learning; Robot Reinforcement Learning; Robot Safety; Safety in Human-Robot Collaboration; Sensor Fusion; Software, Middleware and Programming Environments; Space Robotics and Automation
Autonomous Vehicle Navigation; Formal Methods in Robotics and Automation; Humanoid and Bipedal Locomotion; Hybrid Logical/Dynamical Planning and Verification; Intelligent Transportation Systems; Legged Robots; Model Learning for Control; Motion and Path Planning; Optimization and Optimal Control; Robust/Adaptive Control of Robotic Systems
Primary; Calibration and Identification; Dynamics; Ethics and Philosophy; Robot Companions; Social Human-Robot Interaction; Secondary; Physical Human-Robot Interaction; Domestic Robots; Education Robotics; Energy and Environment-Aware Automation; Entertainment Robotics; Gesture, Posture and Facial Expressions; Human-Centered Robotics; Humanoid and Bipedal Locomotion; Humanoid Robots; Model Learning for Control; Optimization and Optimal Control; Physically Assistive Devices; Robust/Adaptive Control of Robotic Systems; Wearable Robots
Primary Areas: Visual servoing, visual tracking, vision-based control, soft robotics, surgical robotics, robot vision. Secondary Areas: Image-guided medical robots, UAV visual tracking, mobile manipulation, modeling and control of space robots.
Primary area:Dynamics and control, legged and humanoid robots, exoskeletons, model predictive control, trajectory generation and optimization. Secondary area:Physical human-robot interaction, actuator design, system identification and adaptive control.
Andrea M. Zanchettin received his MSc in Computer Science Engineering in 2008, and his PhD in Information Technology in 2012, both from Politecnico di Milano. During Spring 2010, he spent a research stay at the Department of Automatic Control (Reglerteknik) at Lund University. From January 2012 until February 2014, he has been a temporary research assistant at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB). From March 2014 to September 2016, he has been a fixed-term assistant professor at DEIB, where he is now a tenure-track assistant professor. In September 2014, Andrea Zanchettin has been the recipient of the Young Author Best Paper Award, sponsored by the Italian Chapter of the IEEE RAS (I-RAS). Andrea Zanchettin has been member of the IEEE RAS since 2009, and in 2017 he has been elected as Deputy Chair of I-RAS. Andrea Zanchettin is also co-founder of Smart Robots srl, a spin-off company of Politecnico di Milano, and has been co-author of around 50 papers on automatic control and intelligent human-robot interaction.