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Artificial Intelligence for Applied Robotics

Published by SIMTech, 2021-08-26 04:56:02

Description: Programme information

Course Dates: 8 to 10 February 2022

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With the advancement of artificial intelligence (AI) and sensor technology, robots can better perceive and understand dynamic environments. Perception-guided robotic technology is now widely used in autonomous mobile platforms, smart factories and warehouse automation. This course aims to equip participants with the knowledge and tools to deploy intelligent perception approaches to real-world robotic applications. It mainly focuses on the domains of computer vision and motion planning, targeting their applications in collaborative robotics. The sessions are organised to offer a hands-on experience based on python programming, and state-of-art perception libraries. Upon completion of this course, participants gain hands-on experience in building robotic perception technologies and applying their newly learnt skills to practical robotic applications such as bin picking, machine tending, component handling etc. About this Programme The course consists of three components: classroom training, coding practices followed by hands-on practical experience. The basic learning units offer general knowledge about collaborative robots and robotic perception and the advanced learning units equip the participants with relevant coding skills to implement robotic solutions. In addition, the course aims to help participants address the following knowledge gaps: • Able to differentiate between industrial robots and collaborative robots. • Capable of recognising different perception driven approach for industrial and collaborative robots • Capable of integrating perception and motion submodules. • Understand fundamentals of python programming and basic deep learning frameworks. • Identify the key gaps in manufacturing organisations and use collaborative robots to improve the efficiency and effectiveness of automation. • Understand how to use current commercially available tools or software to build autonomous perception applications. • Awareness on transforming their operations into a “Smart Factory” through the adoption of robots and AI technologies. • Know how to perform simulation to verify autonomous perception before execution in a real environment. Who Should Attend This course is recommended for engineers, entrepreneurs and professionals who are interested in robotics working in the areas of manufacturing, supply chain, intelligent system etc. It is a pre-requisite for participants to have basic Python or C++ programming skills.

Course Outline Skills Course Reference Number: To be confirmed (16 training hours) The programme employs the Learn-Practise-Implement™ (LPI™) pedagogy, where fundamental knowledge and principles taught will be reinforced with hands-on practical experience. Industrial/collaborative LEARN- System robot over-view PRACTISE- architecture design IMPLEMENT™ Introduction to perception Submodule integration for for industrial and (LPI™) robotic perception collaborative robots Deployment of perception-based binpicking Robot motion planning and simulation of robotic application by collaborative robots solutions 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$465 (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$1,550 (before GST). For more information about the funding, please visit SkillsFuture Singapore website at www.ssg.gov.sg

About the Trainers Dr Xavier Xie is an Advanced Development Scientist with the Advanced Robotics Application Group at A*STAR Advanced Remanufacturing and Technology Centre (ARTC). He has more than 10 years of research, industry and entrepreneur experience in Robotics and Artificial Intelligence. Dr Xie received his PhD degree in Mechatronics from the Nanyang Technological University in 2017. His research interests include unmanned systems, industrial tool path optimisation and image processing. He is currently focused on helping local companies improve efficiency and innovation capabilities by adopting robotic and AI solutions. He led several robot automation projects, which are successfully implemented in industry and successfully implemented through technological transformation. Last but not least, several robot automation projects which he led were successfully implemented in industry through technology transfer and licensing. Mr Tijo Thayil as Group Manager currently leads the Advanced Robotic Application activities at ARTC. His portfolio includes smart automation, intelligent robotics & software development for robotic industrialisation. With 16 years of experience in the R&D and industrial sectors, he has taken up various roles in organisations including the Nanyang Technological University (NTU), Singapore Institute of Manufacturing Technology (SIMTech), Rolls-Royce etc. Mr Tijo is a PMP-certified project management professional, and holds a Master Degree from the Nanyang Technological University. He is also a CPE-approved lecturer and teaches engineering diploma courses in Singapore CPE-approved institutes. 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: Dr Xavier Xie, Advanced Development Scientist at [email protected] Scan the QR code for more information. 10/2021


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