AIRS in the AIR
AIRS in the AIR | 多机器人系统(四)

多机器人系统由众多独立的机器人个体组成,个体间可自主地协同合作,相比单个机器人具有更高的效率、可扩展性和容错能力,正在改变各行各业应对复杂任务的方式,在物流运输、工业生产和环境监测等诸多领域取得了广泛应用。
AIRS in the AIR “多机器人系统”系列活动邀请世界顶级学者开展讲座,第四期邀请来自剑桥大学和新加坡科技设计大学的学者分享多机器人系统的协同控制策略和异构多机器人应用的相关研究。
Amanda Prorok 是剑桥大学计算机科学与技术系的副教授,她还担任RA-L和AURO副编辑,曾获欧洲研究协会(ERC)启动经费、亚马逊研究奖、牛顿基金会早期职业奖以及多个最佳论文奖等荣誉。
Malika Meghjani 是新加坡科技设计大学计算机科学与设计系助理教授,她带领多智能体机器人视觉和学习(MARVL)实验室研究高效、可靠和可扩展的机器人算法设计,2020年被Analytics Insight评为“机器人领域全球最著名的50位女性”之一。
通过Bilibili(http://live.bilibili.com/22587709)参与。
呼吸新鲜空气,了解前沿科技!AIRS in the AIR 为 AIRS 重磅推出的系列活动,与您一起探索人工智能与机器人领域的前沿技术、产业应用、发展趋势。
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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
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Amanda Prorok剑桥大学副教授Learning Cooperative Control Policies for Multi-Robot Systems
Amanda Prorok is an Associate Professor in the Department of Computer Science and Technology, at Cambridge University, and a Fellow of Pembroke College.
Her lab's research focuses on multi-agent and multi-robot systems. Their mission is to find new ways of coordinating artificially intelligent agents (e.g., robots, vehicles, machines) to achieve common goals in shared physical and virtual spaces. This research brings in methods from machine learning, planning, and control, and has numerous applications, including automated transport and logistics, environmental monitoring, surveillance, and search.
Prior to joining Cambridge, Amanda was a postdoctoral researcher at the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania, USA, where she worked with Prof. Vijay Kumar. She completed her PhD at EPFL, Switzerland, with Prof. Alcherio Martinoli. She has been honored by numerous research awards, including an ERC Starting Grant, an Amazon Research Award, the EPSRC New Investigator Award, the Isaac Newton Trust Early Career Award, and several Best Paper awards. Her PhD thesis was awarded the Asea Brown Boveri (ABB) prize for the best thesis at EPFL in Computer Science. She serves as Associate Editor for IEEE Robotics and Automation Letters (R-AL) and Associate Editor for Autonomous Robots (AURO).
In this talk, I discuss how we leverage machine learning methods to synthesize cooperative policies for multi-agent and multi-robot systems. I describe how we use Graph Neural Networks (GNNs) to model differentiable communications channels, and show how this enables decentralized coordination across various multi-agent tasks. I then describe the sim-to-real gap from a multi-robot perspective, and conclude by discussing the role of agent heterogeneity and its impact on transferring learned cooperative policies to real-world experimental settings.
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Malika Meghjani新加坡科技设计大学助理教授Real-World Applications of Heterogeneous Multi-Robot Sytems
Dr. Malika Meghjani is an Assistant Professor in the Computer Science and Design Pillar at Singapore University of Technology and Design (SUTD). She directs the Multi-Agent Robot Vision and Learning (MARVL) Lab, with the focus on algorithm design for efficient, reliable and scalable robots that can work independently and collaboratively with humans. Her research interests are in planning under uncertainty, reinforcement learning, computer vision, deep learning, and game theory. The applications of her work are in field robotics ranging from marine robots specifically, underwater and surface vehicles to aerial drones and selfdriving cars as well as other ground vehicles in unstructured environments. Malika has been cited by Analytics Insight in 2020 as one of the World's 50 Most Renowned Women in Robotics. She is also 2017 SMART Postdoctoral Scholar, 2015 McGill Scarlet Key recipient, 2013 IEEE Canada Women in Engineering Prize awardee and 2013 Google Anita Borg Scholar.
Real-world applications with multiple objectives can greatly benefit when multi-robot systems are heterogeneous. In this talk, I will present some of the applications for which we use heterogeneous multi-robot systems. These include dynamic environment monitoring, searching for moving and evading targets, mobility-on-demand, and urban reconnaissance. The heterogeneity in the proposed applications is showcased in terms of the robots in different domains as well as robots with different capabilities in the same domain.
时间 | 环节 | 嘉宾与题目 |
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18:00-18:45 |
主题报告 |
Amanda Prorok , 剑桥大学 |
18:45-19:00 |
主题报告 |
Malika Meghjani ,新加坡科技设计大学 |
视频回顾
(Amanda Prorok教授的讲座仅直播无回放)