Apply Autonomous Mobile Robots for Flexible Automation

Mobile robots have been popularly implemented in many commercial and industrial settings, such as logistics, healthcare services, marine, manufacturing, etc.  Many companies are planning to implement autonomous mobile robots to improve their industrial efficiency. With the development of computer science and sensory technology, various types of mobile robots have been designed and developed, such as Autonomous Guided Vehicles (AGVs), Autonomous Mobile Robots (AMRs) and Autonomous Forklifts. Different robots are designed for different tasks, so how to select and configure an appropriate robotic system to serve your application in your environmental setting is an important skill. Robotic engineers must be capable of understanding the robotic fundamentals, selecting the correct mobile robots, designing effective robotic systems, as well as planning their automation projects. This course aims to fill the gaps in knowledge and skills for the manufacturing industry in the areas of autonomous mobile robots. About this Programme The course aims to help participants understand and improve the ability from the following aspects: • Identify the hardware components in a mobile robotic system and their functionalities. • Identity and understand the sensors typically used in mobile robotic systems. • Learn the fundamentals of navigation, perception & control for mobile robotics, including its programming and simulation. • Understand the software modules in a robotic system. • Design your own autonomous robotic system according to the specified applications. • Know some real-life examples of mobile robotic systems in the industry. Understand the common robotic systems, their typical industrial applications Who Should Attend The course is suitable for those who are currently employed or wish to be employed in robotics or industrial automation fields. A typical candidate profile could be: A typical Candidate Profile could be: • R&D Engineers and/or Managers • Software Programmers • Manufacturing Engineers • Automation Engineers • Robotic Integrators • Industrial Design Engineers

Course Outline Skills Course Reference Number: To be confirmed (32 training hours) The programme employs the Learn-Practise-Implement™ (LPI™) pedagogy with 4 learning areas that are aimed to increase the participants’ level of understanding of the fundamentals and skills of mobility robotic systems. Overview of mobile LEARN- Introduction to the robotic systems PRACTISE- software framework of IMPLEMENT™ mobile robotic systems Introduction to sensing for mobile robotics (LPI™) Real-life applications of mobile robotics in industry and manufacturing Upon Completion of the Programme Participants will be awarded with a certificate of attendance by ARTC. Course Fee and Funding • The nett course fee for all Singaporeans and SPRs aged 21 years old and above is S$780 (before GST). • Employees fully sponsored by SMEs can claim an additional 20% of the full course fee with the Enhanced Training Support for SMEs Funding scheme (ETSS), subject to approval by SSG. • Singaporeans aged 40 years and above can claim an additional 20% of the full course fee with the Mid-Career Enhanced Subsidy (MCES). • Singaporeans aged 25 years old and above are eligible for SkillsFuture Credit which can be used to offset course fees (for self-sponsored registrations only). • The full course fee before funding is S$2,600 (before GST). For more information about the funding, please visit SkillsFuture Singapore website at www.ssg.gov.sg

About the Trainers Dr Guan Mingyang is the Development scientist with the Advanced Robotics Application Group at Advanced Remanufacturing and Technology Centre (ARTC). He received his PhD degree from Nanyang Technological University in 2020. His research topics include sensor fusion, SLAM, visual object tracking and machine learning. Dr Guan has over 7 years of research and development experience on autonomous mobile robots. He has plenty of knowledge on various kinds of mobile robots, such as Husky robot, Fetch robot, Kuka robot and manipulator. He has developed some prototype of robotic systems, such as differential wheeled wheelchair and autonomous Road-sweeper, which have been successfully implemented in industry. Mr Tijo Thayil currently leads the Advanced Robotic Application activities at ARTC, as Group Manager. The portfolio includes smart automation, intelligent robotics & software development for robotic industrialization. With 16 years of experience in the R&D and industrial sectors, he has taken up various roles in organisations including Nanyang Technological University (NTU), Singapore Institute of Manufacturing Technology (SIMTech), Rolls-Royce etc. Mr Tijo is a PMP-certified project management professional, and holds Master’s Degree from Nanyang Technological University. He is also a CPE-approved lecturer and teaches engineering diploma courses in Singapore CPE-approved institutes. Dr Alberto De San Bernabe is a Team Lead for the Advanced Robotics Applications Group with A*STAR ARTC, driving a multi-cultural team of engineers and scientists to develop robotic solutions for manufacturing and logistics industries. His research interest includes mobile robotics, human-robot interaction, information fusion, localization systems, wireless sensor networks, and computer vision. Ms Lee Li Zhen is a Technical Lead for the Advanced Robotics Applications Group with A*STAR ARTC. With her years of experience in industrial robotics and automation, mobile manipulation, computer vision and software engineering, she leads a team of engineers and scientists to design and develop robotic solutions across various industries. When and Where Dates: Please visit our website at www.a-star.edu.sg/ARTC/KTO for the course schedule. Time: 9.00am to 6.00pm Venue: Advanced Remanufacturing and Technology Centre (ARTC) 3 CleanTech Loop, #01/01, CleanTech Two, Singapore 637143 Registration Please register online at www.a-star.edu.sg/ARTC/KTO Contact Us For general enquiries, please contact: Dr Edwin Soh, Senior Business Development Manager at [email protected] For technical information, please contact: Scan the QR code Dr Guan Mingyang, Development Scientist at [email protected] for more information. 10/2021