Date: 13:00-13:45, Monday, 10th July 2023
Location: Room 316
Title: NOKOV's Optical Motion Capture: Exploring Applications and Advancements in Automation and Robotics Research
Lecturer: Peng Gao

Abstract:
In this seminar, NOKOV, a leading manufacturer of optical motion capture systems in China, will delve into the applications of Motion Capture systems in automation research. The discussion will cover the broad applications of motion capture technology across various sectors, with a focus on case studies in human-machine collaboration, robotic assembly, UAVs and AUVs, exoskeletons, and end effector control. Attendees will gain insights into the precise 3D motion capture capabilities of NOKOV's systems, their extensive adoption in the research community, and their role in cutting-edge research projects. This seminar is an essential opportunity for those interested in the intersection of technology and research, and eager to understand how motion capture is shaping the future of automation.

Date: 15:00-15:45, Monday, 10th July 2023
Location: Room 317
Title: Quick Win Solution for GHG Emission Reduction "RENKEI CONTROL" for Factories, Buildings and Cities
Lecturer: MIKE SUZUKI

Abstract:
The equipment used in factories, buildings and city is consuming energy and emitting GHG for production. 
The operation of the equipment in these target systems has big impact on overall energy efficiency and amount of GHG emissions.
It is important to see the whole picture to achieve improvement in the overall energy efficiency with optimal operation of equipment in these target systems instead of focusing on the performance of individual equipment. ""RENKEI Control"" is the IoT solution to see the whole picture and provide the optimal solution with short implementation period. ""RENKEI"" is the Japanese word for coordination. ""RENKEI Control"" is optimally coordinating the operations of multiple equipment in the target systems to work seamlessly together as a whole picture to achieve the target objective through control. It also has the flexibility to adapt to the ever changing in conditions such as changes in energy demand, renewable energy supply and introduction of new type of fuels and equipment, which will certainly happens in the future. Hence, the implementation of RENKEI Control can optimize the operation of target system for improvement in overall energy efficiency and realizing the quick-win to reduce GHG emissions in line with the ever changing conditions.  
This presentation will introduce concept of RENKEI control and actual implementation example of RENKEI Control for GHG emissions reduction. "

Date: 12:00-12:45, Wednesday, 12th July 2023
Location: Room 316
Title: Online Hands-on Control Experience for Freshmen: User-Friendly Simulators and Virtual Experiments
Lecturer: Mitsuji Sampei (Tokyo Institute of Technology)

Abstract:
The School of Engineering at Tokyo Institute of Technology offers freshmen the opportunity to experience various fields of engineering, including electrical, electronic, mechanical, systems, control, and information engineering. The Department of Systems and Control Engineering offers a hands-on feedback control experience on a LEGO MINDSTORMS line-trace robot. In 2020, the Covid-19 pandemic forced us to perform such experiences online.
Our online course consists of virtual experiments and simulators. As a virtual experiment, videos were prepared in advance showing how the robot performs line-tracing for a set of pre-selected gain parameters, and the students selected the video according to their parameter tuning strategies. Thus, they experienced parameter tuning as if they were conducting real experiments, but the number of videos was limited. Thus, we needed user-friendly simulators that would allow students to try out as many parameters as they wanted. We used MATLAB App Designer to develop such simulators.
Many students commented that it was regrettable that they could not conduct the actual experiments due to Covid-19, but that they enjoyed the experience of parameter tuning through the virtual experiments in this course. In this presentation, we will introduce our online course, especially the simulators developed with the MATLAB App Designer.

Date: 13:00-13:45, Wednesday, 12th July 2023
Location: Room 318
Title: Introduction of case studies of YOKOGAWA AI-related achievements and AI products

Lecturer: Hirotsugu Gotou (Yokogawa Electric Corporation), Mr.Keiichiro Kobuchi (Yokogawa Digital Corporation)
Abstract:
Yokogawa is actively working on AI control in plants as a next-generation control technology that can reduce environmental impact, stabilize quality, and achieve work style reform.
Jointly developed by Yokogawa and the Nara Institute of Science and Technology (NAIST), FKDPP is an autonomous control AI protocol that makes use of reinforcement learning technology. 
It can control and autonomize areas of plant operations that have been beyond the capabilities of existing control methods and have up to now necessitated manual operation. 
Yokogawa put FKDPP into practical use by utilizing the company's know-how regarding plant operation and control, and successfully autonomized manual operations of a distillation column during a field test at a chemical plant. 
FKDPP inventors Yokogawa and NAIST, as well as Yokogawa Digital, the Yokogawa subsidiary, are joint recipients of the award.
In this seminar, we will introduce those Yokogawa AI control technologies and related AI products. 

Date: 13:00-13:45, Wednesday, 12th July 2023
Location: Hall A
Title: NOKOV's Optical Motion Capture: Exploring Applications and Advancements in Automation and Robotics Research
Lecturer: Peng Gao
Abstract:
 In this seminar, NOKOV, a leading manufacturer of optical motion capture systems in China, will delve into the applications of Motion Capture systems in automation research. The discussion will cover the broad applications of motion capture technology across various sectors, with a focus on case studies in human-machine collaboration, robotic assembly, UAVs and AUVs, exoskeletons, and end effector control. Attendees will gain insights into the precise 3D motion capture capabilities of NOKOV's systems, their extensive adoption in the research community, and their role in cutting-edge research projects. This seminar is an essential opportunity for those interested in the intersection of technology and research, and eager to understand how motion capture is shaping the future of automation.

Date: 14:00-14:45, Wednesday, 12th July 2023
Location: Hall A
Title: Safety analysis of AI systems based on composite methodology of FRAM and SpecTRM
Lecturer: Hideki Nomoto

Abstract:
This presentation explains the new methodology to verify safety of black-box type of artificial intelligence (AI) such as deep neural network (DNN). In the proposed methodology, the following two key technologies are used:
- FRAM (Functional Resonance Analysis Method)
- SpecTRM (Specification Tools and Requirement Methodology) FRAM will be used to visualize the hidden internal logic inside the DNN which is supposed to be acquired during the machine learning (ML) process.
SpecTRM will be used to analyze the ML test result and tune-up/validate the FRAM model to show completeness of the ML and consistency of the trained DNN model.
By this study, the following findings were acquired:
1)　The hidden internal logic of DNN system can be effectively visualized by FRAM by its rich modeling capability to define classification task analysis.
2)　Formal method technology (SpecTRM) can be used to check consistency of the FRAM model and validate that the trained AI logic is understandable for human.
3)　Formal method technology (SpecTRM) can be used to check completeness of the ML by confirming full-path testing is completed and by identifying all missing test cases.
4)　The proposed methodology can be utilized not only for black-box type of AI, but also applicable to white-box type of AI such as random forest systems.

International Patent
Japan 7007529
US  11593253 B3
China ZL202080058982.3
Korea 10-2442416

Date: 15:00-15:45, Wednesday, 12th July 2023
Location: Hall A
Title: Resources for Instructors Teaching Controls Courses and Labs
Lecturer: Craig Buhr (Engineering Manager, Control Design Products)

Abstract: 
Resources for Instructors Teaching Controls Courses and Labs                                               ]
Summary:    In this talk, we will give an overview of various resources for instructors teaching dynamics and controls courses: (1) MATLAB Tech Talks are short educational videos that teach complex controls concepts to students and can help supplement instructors’ curriculum materials.(2) MATLAB Grader lets instructors create interactive course assignments and automatically grade the MATLAB code. Instructors can build MATLAB coding problems and store them in collections. (3) Onramps are free self-paced tutorials that help students learn the fundamentals of MATLAB, Simulink, control design, reinforcement learning and many more topics and tools. (4) MATLAB Online makes teaching and learning convenient by providing access to MATLAB and Simulink from any browser. The session will also highlight controls curriculum, virtual labs, and low-cost hardware projects developed by instructors.  "

Date: 13:00-13:45, Thursday, 13th July 2023
Location: Hall A
Title: Introduction of case studies of YOKOGAWA AI-related achievements and AI products
Lecturer: Hirotsugu Gotou (Yokogawa Electric Corporation), Mr.Keiichiro Kobuchi (Yokogawa Digital Corporation)

Abstract:
Yokogawa is actively working on AI control in plants as a next-generation control technology that can reduce environmental impact, stabilize quality, and achieve work style reform.
Jointly developed by Yokogawa and the Nara Institute of Science and Technology (NAIST), FKDPP is an autonomous control AI protocol that makes use of reinforcement learning technology. 
It can control and autonomize areas of plant operations that have been beyond the capabilities of existing control methods and have up to now necessitated manual operation. 
Yokogawa put FKDPP into practical use by utilizing the company's know-how regarding plant operation and control, and successfully autonomized manual operations of a distillation column during a field test at a chemical plant. 
FKDPP inventors Yokogawa and NAIST, as well as Yokogawa Digital, the Yokogawa subsidiary, are joint recipients of the award.
In this seminar, we will introduce those Yokogawa AI control technologies and related AI products. 

Date: 14:00pm-14:45, Thursday, 13th July 2023
Location: Hall A
Title: Collaborative Robot with Ease of Use even for First-time Robot Users
Lecturer: Masahiro Morioka (Chief Engineer, Robot Mechanical Development Laboratory, Robot Business Division< FANUC CORPORATION)

Abstract:
At manufacturing sites facing labor shortages, where automation that can improve productivity even with a small number of workers is needed, the demand for collaborative robots that can work with humans without safety fences is rapidly increasing. In this seminar, we will introduce the features and application examples of collaborative robots with ease of use even for first-time robot users.

Date: 16:00-16:45, Thursday, 13th July 2023
Location: Hall A
Title: Leading the Future of Product Development: Revolutionizing Control Development with CYBERNET SYSTEMS
Lecturer: Shintaro OSAJIMA

Abstract:
In recent years, control development corresponding to electrification and automation has become increasingly complicated in product development, and it has become difficult to deal with unforeseen problems such as failures with conventional development methods. Improving the efficiency of development is an urgent issue. CYBERNET provides technical supports for MBSE and MBD, as well as new fields such as 3D CAE, Visualization, IoT/XR, Digital Twins, and AI, based on the technologies it has cultivated as a leading CAE company. In this presentation, we will introduce the strengths of CYBERNET deployed globally and control development solutions that are actually helpful for development and manufacturing sites.

Date: 13:00-13:45, Friday, 14th July 2023
Location: Hall A
Title: Case studies of AI solution in AISIN corporation
Lecturer: Nagata Yusuke

Abstract:
AISIN corporation is a global supplier of automotive components.
We present case studies of AI solution in the factory, design, and product areas with some movies