AIRS in the AIR

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  林天麟

  AIRS 智能机器人中心主任、香港中文大学（深圳）助理教授

  执行主席

  嘉宾介绍

  个人简介
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  高源

  AIRS 智能机器人中心助理研究员

  主持人

  嘉宾介绍

  个人简介
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  Paolo Robuffo Giordano

  IRISA 实验室 CNRS 高级研究员

  Control, State Estimation and Human Interaction for Multi-Robot Groups

  嘉宾介绍

  Paolo Robuffo Giordano is a CNRS senior research scientist head of the Rainbow group at IRISA/Inria, Rennes, France. He holds a PhD degree in Systems Engineering obtained in 2008 at the University of Rome “La Sapienza”. From January 2007 to July 2007 and from November 2007 to October 2008, he was a research scientist at the Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Germany, and from October 2008 to November 2012 he was a senior research scientist at the Max Planck Institute for Biological Cybernetics and scientific leader of the group “Human-Robot Interaction”. His scientific interests include motion control for mobile robots and mobile manipulators, visual control of robots, active sensing, bilateral teleoperation, shared control, multi-robot estimation and control, aerial robotics.

  个人简介

  Research on multi-robot systems has flourished over the last decades with a number of theoretical and experimental results also made possible by the constant technological advancements in onboard sensing, communication and computing power. A scenario that still motivates considerable research efforts is that of decentralized formation control of multiple mobile robots based on only local (onboard) sensing and communication, with the aim of deploying highly autonomous robot teams in "non-trivial" environments (e.g., inside buildings, underwater, underground, or even in deep space) where centralized measuring/communication facilities (such as GPS) are not available. Furthermore, in many situations an interaction with a human operator is desirable (and desired).

  In this talk, I will review several recent results involving decentralized formation control and localization for groups of robots that mainly rely on onboard sensing and (when necessary) local communication. I will also describe how the group autonomy and redundancy can be effectively coupled with a remote human operator in charge of giving high-level commands and receiving a visual/haptic feedback informative of the robot status. Experiments with quadrotor UAVs will finally help assessing how the various theoretical and algorithmic contributions actually perform in realistic settings.

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  David Navarro-Alarcon

  香港理工大学助理教授

  On Shapes, Robots, and Sensor-Based Controls

  嘉宾介绍

  David is an Assistant Professor with the Department of Mechanical Engineering of The Hong Kong Polytechnic University, and the Principal Investigator of the Robotics and Machine Intelligence Laboratory (ROMI-Lab). His research mostly focusses on modelling and control of robot motion tasks. The constant goal of his work has been the establishment of methodologies that provide robots with advanced sensorimotor capabilities. David is a Senior Member of the IEEE and currently serves as an Associate Editor of the IEEE Transactions on Robotics (T-RO).

  In 2014, David received his PhD degree in mechanical and automation engineering from The Chinese University of Hong Kong (CUHK), where he was supervised by Prof. Yun-hui Liu, and received the prestigious CONACYT Fellowship during his doctoral studies. David worked from 2014–2017 at the CUHK T Stone Robotics Institute, first as a Postdoctoral Fellow and then as a Research Assistant Professor.

  At PolyU, David teaches subjects on robotics, nonlinear dynamics, and automatic control. He has received various teaching awards and has led several teaching initiatives on the development of “digital robotic platforms for online education”.

  个人简介

  The goal of this talk is to share recent research results from my group at PolyU on the development of sensor-based methods to guide the motion of various robotic systems. I will begin by presenting our pioneering work on visual shape servoing of deformable/soft objects, a problem that has become one of the most popular and active topics in robotics in recent years. I will then show how we used our work with variable morphologies to develop a new class of soft-rigid mobile agents with the capability to actively change its morphology, hence, enabling them to conform to different shapes and objects. Other applications of our sensor-based control methodology will also be discussed, e.g., new Fourier-based formation controls of robots into parametric contours, autonomous foraging of robotic insects using artificial pheromones, vision-based cosmetic dermatology robots, robot thermal servoing as a new paradigm for robot motion, ultrasound-based navigation for robotic scoliosis, among others. The performance of these methods will be illustrated with several experimental videos.

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