南开大学人工智能与机器人国际学术讲坛

Nankai University International E-Forum on Artificial Intelligence and Robotics

第四期

l 2020年11月24日（周二） 腾讯会议：431 345 623

12:30-13:30

报告题目：Robust Perception for Robots: Sensor Fusion from Algorithm to Device Design

l 2020年11月28日（周六） 腾讯会议：742 712 420

13:45-14:45

报告题目：智能化可穿戴系统Intelligent wearable systems

报告12：

报告时间：2020年11月24日（周二）12:30-13:30

腾讯会议：431 345 623

报告题目：Robust Perception for Robots: Sensor Fusion from Algorithm to Device Design

Abstract：Combining multiple sensor modalities to achieve more robust understanding of environment and robot status is an emerging research area in robot navigation and autonomous driving. To fuse sensors such as camera, lidar, inertial measurement unit (IMU), wheel encoder, etc., one must solve problems in synchronization, calibration, signal correspondence, and data fusion. In this talk, I will discuss the recent progress that we have made in sensor fusion to address many problems in autonomous driving and robot navigation using autonomous motorcycle and NASA Robonaut as examples. We will also discuss how augmented reality development on mobile devices benefit from the sensor fusion approach in robotics. Moreover, addressing perception challenges after sensory data are collected from individual modalities may limit perception potential; I will talk about sensor fusion at device level where we combine different sensory modalities into a single device to achieve new promising capabilities in applications such as underwater communication & ranging, and robotic grasping.

Biography：

Dezhen Song is a Professor and Associate Department Head for Academics with Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA. Song received his Ph.D. in 2004 from University of California, Berkeley; MS and BS from Zhejiang University in 199 and 1995, respectively. Song's primary research area is robot perception, networked robots, visual navigation, automation, and stochastic modeling. He received NSF Faculty Early Career Development (CAREER) Award in 2007.  From 2008 to 2012, Song was an associate editor of IEEE Transactions on Robotics (T-RO). From 2010 to 2014, Song was an Associate Editor of IEEE Transactions on Automation Science and Engineering (T-ASE). From 2017 to 2020, Song was a Senior Editor for IEEE Robotics and Automation Letters (RA-L). He is also a multimedia Editor and chapter author for Springer Handbook of Robotics. Dezhen Song has been PI or Co-PI on more than $14.0 million in grants including more than $4.0 million from NSF. His research has resulted in one monograph and more than 110 refereed conference and journal publications.

报告13：

报告时间：2020年11月28日（周六）13:45-14:45

腾讯会议：742 712 420

报告题目：智能化可穿戴系统Intelligent wearable systems

报告摘要：在大数据背景下的智能衣（可穿戴系统）和物联网的融合，对人体特征的实时监控极为重要，可提供面向人体的全方位的数字服务，包括：1）建立以智能衣为基础的健康诊断系统（medical diagnosis systems using intelligent garments），2）特殊效果的时尚设计 （fashion design with special effects），3）防护、安全和风险管理 （protection, security and risk management），4）个性化体育运动管理（personalized sport management），5）人机协作和协调 （cooperation and coordination），6）人体大数据的收集和学习（human body data collection and learning）。本讲座以所在团队开发的面向孕妇诊断智能服装和智能化消防衣为案例，系统化介绍智能衣基本概念、系统框架、产品设计、柔性传感器原理、决策软件系统设计、生理信号的处理方法以及相关云平台专家系统的设计。

报告人简介：

报告专家为法国里尔科技大学自动化博士、法国国立高等纺织工程师学院特级教授、法国GMETEX国家实验室主任，纺织管理和产品设计系主任，IEEE Senior Member, 法国北方自动化学会人机交互分会主席，ICJIS国际期刊副主编，南开大学、苏州大学、东华大学和西南交通大学的顾问教授，中国卓越工程师项目主讲。长期从事数字时尚、人机交互和时尚产品的计算机辅助设计和生产管理的工作，特别是专注在纺织大数据分析、建模和感性产品设计以及可穿戴系统设计方面的研究，共培养30余名博士生。曾经发表论文350余篇，包括130余篇SCI检索的国际一流期刊和200余篇在国际一流会议上宣读的论文。自2000年以来，获得了欧盟科技H2020，教育Ersmus Mundus多个项目的基金支持，也获得法国国家科研开发项目ANR和国家工业研发支撑项目FUI的支持，更获得20多个法国和国际大企业的直接资助，共完成30多个项目，项目总金额达到1000万欧元以上。同时还经常被邀请赴捷克，罗马尼亚，突尼斯从事讲学，并和澳大利亚的悉尼科技大学保持长期合作关系。