Seminars in Robotics
We are living in the twenty-first century with tremendous progress in science and technology, which enables us to produce abundance of supplies. However, the international conflicts do not seem to be diminished in line with the intensified creation of wealth. What should be the root cause behind such phenomenon? The answer comes from the disparity of cultures among nations, populations, and races, etc. Interestingly, there is a universal culture space which is three-dimensional and has three axes for measuring universal values in our common world. In this talk, I will sequentially answer these six questions, namely: Who are we? Where are we come from? Where are we going to? Who is the designer of human beings? Who are the producers of human beings? Who are the users of human beings? The answers to the last three questions will help us to understand the universal culture space and value systems. Hopefully, the wide adoption of such findings will bring durable peace on our Earth.
Schedule: December 25-28, 2022
For more update, please visit: I-SEEC & ICTSS 2022 (e-jikei.org)
26 August 2022 (Friday), 2pm – 3pm
Lecture Theatre 7A (LT 7A)
NUS College of Design and Engineering
9 Engineering Drive 1, Singapore 117575
OceanOneK is a robotic diver with a high degree of autonomy for physical interaction with the environment while connected to a human expert through an intuitive interface. The robot was recently deployed in several archeological expeditions in the Mediterranean with the ability to reach 1000 meters. Distancing humans physically from dangerous and unreachable spaces while connecting their skills, intuition, and experience to the task.
About the Speaker
Oussama Khatib received his PhD from Sup’Aero, Toulouse, France, in 1980. He is Professor of Computer Science and Director of the Robotics Laboratory at Stanford University. His research focuses on methodologies and technologies in human-centered robotics, haptic interactions, artificial intelligence, human motion synthesis and animation. He is President of the International Foundation of Robotics Research (IFRR) and a Fellow of the Institute of Electrical and Electronic Engineers (IEEE). He is Editor of the Springer Tracts in Advanced Robotics (STAR) series, and the Springer Handbook of Robotics, awarded the American Publishers Award for Excellence in Physical Sciences and Mathematics. He is recipient of the IEEE Robotics and Automation (IEEE/RAS) Pioneering Award (for his fundamental contributions in robotics research, visionary leadership and life-long commitment to the field), the IEEE/RAS George Saridis Leadership Award, the Distinguished Service Award, the Japan Robot Association (JARA) Award, the Rudolf Kalman Award, and the IEEE Technical Field Award. Professor Khatib is a member of the National Academy of Engineering
Please register your attendance by 24 August 2022: https://forms.office.com/r/YGuZ9Nwmih
Organised by NUS Advanced Robotics Centre
Co-Sponsor and Co-Organizer: IEEE Robotics and Automation Society Singapore Chapter
More detail could be found at: https://eeeai.xmum.my/forum/
To Join The Online Forum, Kindly Click The Link below.
Join Zoom Meeting
Meeting ID: 812 1769 9608
Deep learning is a very powerful methodology which can solve many AI problems. There are a number of problems with it, though, including a lack of transparency and a lack of generalizability from one data set to another. In addition, it often requires a great deal of data for training and can be very expensive computationally. In this talk, we will discuss some investigations into the behavior of deep learning, and suggest some approaches to deal with the problems mentioned above.
Professor Carlsson is Professor Emeritus and Ann and Bill Swindells Professor at Stanford University. He received his PhD from Stanford University. His previous affiliations include the University of California, San Diego and Princeton University. He is Fellow of the American Mathematical Society (2017). He held a Alfred P. Sloan Fellowship (1983-1987). He gave a Whittaker Colloquium at the University of Edinburgh, and Rademacher Lectures at the University of Pennsylvania in 2011. He gave a keynote lecture at the Inaugural conference for Computational Instute, University of Illinois, Urbana-Champaign in 2012. He founded the AI INc. Ayasdi Inc. (2008) and UnBox AI (2019). His research interests include algebraic topology, algebraic K-theory, topology and number theory.
Date and time
26 July 2022, 10–11am Singapore (GMT+8)
Joint IMS-IAS Public Lecture, July 2022 (office.com)
Speaker: Associate Professor Xie Ming
Time: 1:30pm - 2:30pm | Venue: SUTD, CC9, Building 2, Level 3, Room 7
The first industrial revolution was characterized by fully machine-integrated manufacturing since 1784, while the second industrial revolution was characterized by fully production-line-integrated manufacturing since 1923. Since 1969, the third industrial revolution was characterized by fully computer-integrated manufacturing. During the period from 2011 to 2013, we have entered the era of fourth industrial revolution, which was characterized by fully network-integrated manufacturing. In parallel, we are gradually evolving into the fifth industrial revolution, which will be characterized by fully robot-integrated manufacturing. The aim of such evolution is to achieve manufacturing as agile as possible with the help of massive deployment of sensors, actuators, networks, robots, and cloud computing.
In this keynote speech, the speaker will talk about: a) the landscape of manufacturing and industrial revolutions, b) the landscape of robotics and automation, and c) the roadmap of robotics applications for achieving robot-integrated manufacturing.
Robot-Integrated Manufacturing | SkillsFuture 2022 (sutd.edu.sg)
Wednesday 30 March 2022 - 11:00-12:30 online via Zoom
Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block opponents while operating their vehicles at their traction limits. Racing simulations, such as the PlayStation game Gran Turismo, faithfully reproduce the non-linear control challenges of real race cars while also encapsulating the complex multi-agent interactions. Here we describe how we trained agents for Gran Turismo that can compete with the world’s best e-sports drivers. We combine state-of-the-art, model-free, deep reinforcement learning algorithms with mixed-scenario training to learn an integrated control policy that combines exceptional speed with impressive tactics. In addition, we construct a reward function that enables the agent to be competitive while adhering to racing’s important, but under-specified, sportsmanship rules. We demonstrate the capabilities of our agent, Gran Turismo Sophy, by winning a head-to-head competition against four of the world’s best Gran Turismo drivers. By describing how we trained championship-level racers, we demonstrate the possibilities and challenges of using these techniques to control complex dynamical systems in domains where agents must respect imprecisely defined human norms.
More details at: https://www.plymouth.ac.uk/research/robotics-neural-systems/whats-on
The Center for Robotics and Neural Systems (CRNS) is pleased to announce the talk of Dr. Séverin Lemaignan who is a senior scientist at PAL Robotics, Spain on Wednesday, March 2nd from 11:00 am to 12:30 pm (London time) over Zoom.
>> Events: The CRNS talk series will cover a wide range of topics including social and cognitive robotics, computational neuroscience, computational linguistics, cognitive vision, machine learning, AI, and applications to autism. More details are available here:
>> Link for the next event (No Registration is Required):
>> Title of the talk: Teaching robots autonomy in social situations
Participatory methodologies are now well established in social robotics to generate blueprints of what robots should do to assist humans. The actual implementation of these blueprints, however, remains a technical challenge for us, roboticists, and the end-users are not usually involved at that stage.
In two recent studies, we have however shown that, under the right conditions, robots can directly learn their behaviours from domain experts, replacing the traditional heuristic-based or plan-based robot controllers by autonomously learnt social policies. We have derived from these studies a novel 'end-to-end' participatory methodology called LEADOR, that I will introduce during the seminar.
I will also discuss recent progress on human perception and modeling in a ROS environment with the emerging ROS4HRI standard.
Unmanned systems have applications in many areas such as surveillance, transport, structure inspection, logistics, etc. Perception and localization are essential capabilities of unmanned systems. There have been a lot of studies on perception and localization based on various sensors such as camera and LiDAR. Each type of sensor has its pros and cons. Different application scenario will require different sensors and there is no one-size-fits-all solution. To achieve accurate and reliable localization in complex environments, heterogeneous sensor fusion has been a recent trend and attracted significant interest. In this talk, we shall present some recent development and discuss possible future directions of the area. The applications of unmanned systems in structure inspection and logistics will be demonstrated.
Dr Xie Lihua is a professor in the School of Electrical and Electronic Engineering, Nanyang Technological University and Director, Center for Advanced Robotics Technology Innovation (CARTIN). He had served as Head of Control and Instrumentation Division and Director of Delta-NTU Corporate Laboratory for Cyber-Physical Systems. His research areas include control engineering, indoor positioning, and unmanned systems. He has authored and co-authored 9 books, over 500 journal and 380 conference articles, and 20 patents/technical disclosures. He was listed as a highly cited researcher annually from 2014 to 2020. He has secured over $90M research funding as programme and project PI. He is currently an Editor-in-Chief of Unmanned Systems and has served as an Editor of IET Book Series on Control and Associate Editor of IEEE Transactions on Automatic Control, Automatica, IEEE Transactions on Control Systems Technology, IEEE Transactions on Control of Network Systems, etc. He was an IEEE Distinguished Lecturer (2011- 2014). Professor Xie is a Fellow of IEEE, a Fellow of IFAC, and a Fellow of Academy of Engineering Singapore.
Venue: Online Zoom Meeting Wednesday, 23 February 2022 10:00 am – 11:00 am
(Registration starts at 9:45 am)
Register at URL: https://bit.ly/3A5XWNt
We are pleased to invite you to attend the Singapore Centre for 3D Printing (SC3DP) Inspiring Ideas Webinar Series on “Future of Additive Manufacturing - Grand Challenges”.
What does it take for Additive Manufacturing (AM) to move beyond? The second webinar will continue explore the grand challenges of AM and its potential for growth. There will be three talks followed by a panel discussion. The session will be moderated by Prof Paulo Bartolo, SC3DP Executive Director.
The monthly Inspiring Ideas Webinar Series aims to cover the different aspects of AM, drawing insights from global academic and industry thought-leaders to generate discussion and action on the advancement of AM technology and its integration into the emerging suite of Industry 4.0 digital technologies.
Please see below for the registration link and more details on the webinar. We look forward to your participation.
10 December 2021, Friday
4.00pm – 5.30pm (SGT / GMT+8:00)
(Zoom link will be provided in confirmation email after registration)
Visit event page
December 10th, 2021 - 9am PT | 5pm GMT | 6pm CET
Zoom Registration link: https://us02web.zoom.us/meeting/register/tZ0lf-uhqTkuHtyRsq87OhXs40KLKNwDmieg
*The talk and discussion will be recorded and shared publicly. Registration is free (and mandatory).
Krishna Murthy, University of Montreal
Evaluating Robot Task Planning Over Large 3D Scene Graphs
Krishna Murthy is a PhD candidate at the Robotics and Embodied AI lab and Mila at the University of Montreal, working on differentiable adaptations of physical processes (computer vision, robotics, graphics, physics, and optimization) and their applicability in modern learning pipelines. His work has been recognized with an NVIDIA graduate fellowship (2021) and a best paper award from Robotics and Automation letters (2019). He was also chosen to the RSS Pioneers cohort in 2020.
Google Scholar: https://scholar.google.co.uk/citations?user=kcr8134AAAAJ
Papers covered during the talk
· Project page: https://taskography.github.io/
Talking Robotics is a series of virtual seminars about Robotics and its interaction with other relevant fields, such as Artificial Intelligence, Machine Learning, Design Research, Human-Robot Interaction, among others. We aim to promote reflections, dialogues, and a place to network.
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