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Course Overview

Leveraging on a range of autonomous robotics cells deployed at the smart factory within Temasek Polytechnic Advanced Manufacturing Centre, this course focuses on vision-assisted robotics technology with integration of the machine vision systems as the smart sensors onto industrial robots as an enabling technology for specific advanced manufacturing applications such as assembly, dismantling and packaging of products. A Vision Guided Robot System is essentially a robot configured with a set of industrial cameras and image processing units as the input devices to provide a secondary feedback signal for a robot to move accurately to a range of varied target positions. This is crucial for a robot to identify the exact location and orientation of a component dispatched by a part feeder for it to pick up within the confined area.

Entry Requirements

Participants should have relevant working experiences in manufacturing sector.

Who Should Attend

Engineers, Technology Specialist

What You'll Learn

Describe the key concepts of integrating machine vision systems in robotics and automation

  • Explain the goals of integrating machine vision systems in robotics and automation
  • Describe the main components of machine vision systems according to the work environment and requirements
  • Distinguish between image processing and image analysis

Apply image analysis techniques in machine vision systems

  • Describe elementary object recognition and identification by features
  • Compare scene analysis and mapping
  • Apply the detection and localization of edges
  • Describe stereo imaging techniques in machine vision system
  • Describe specialized lighting techniques in depth measurement

Develop a machine vision and pattern recognition application

  • Identify the appropriate applications for vision guided robotics application
  • Perform the setting up of a machine vision system to acquire an image
  • Set the boundary conditions of machine vision system for robotics and automation
  • Develop a machine vision assisted robotics application for pattern recognition and inspection.

 

 

Assessment

 

Written test, online quiz, oral assessment

 

 

Level

 

Intermediate

 

 

Certification

 

Participants will be issued with a Certificate of Performance upon meeting 75% of the required course attendance.

Career Opportunities

Automation Engineer, Robotics Engineer, Machine Vision Specialist

Course Schedule/Apply

Intake Info Application Closing Date Course Duration

07 – 08 November 2023

To be advised

2 days

9.00am – 5.00pm

Register Interest

Registration may be closed earlier due to overwhelming response.

 

For Corporate training, click here.

 

Please write to tsa_shortcourse@tp.edu.sg to be included in the course waitlist for future intakes.

Course Fees

Fees Type Course Fees
(w GST) 
Singapore Citizens
Full Course Fee / Repeat Students S$856.00
Aged 40 and above / SME-sponsored S$96.80
Aged below 40 S$256.80
Non-Singapore Citizens
Full Course Fee / Repeat Students S$864.00
Singapore Permanent Residents / Long-Term Visit Pass Plus (LTVP+) Holder S$259.20
SME-sponsored (Singapore Permanent Residents) / Long-Term Visit Pass Plus (LTVP+) Holder) S$99.20

SkillsFuture Credit Approved. For more details, please click here


With effect from 1 Jul 2020, the Workforce Training Scheme (WTS) will be replaced by the Work Support Scheme (WSS), for more information, please visit:
https://www.wsg.gov.sg/programmes-and-initiatives/workfare-skills-support-scheme-individuals.html

Lecturer/Trainer Profile

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Course Contact

  • 67881212
  • Monday - Thursday: 8:30am - 6:00pm
    Friday: 8:30am - 5:30pm
     
    Closed during lunchtime, 12:00pm - 1:00pm
    and on weekends and public holidays.

  • https://www.tp.edu.sg/tsa
  • Temasek SkillsFuture Academy (TSA)
    Temasek Polytechnic
    East Wing, Block 1A, Level 3, Unit 4
    21 Tampines Ave 1
    Singapore 529757

     

  • Temasek Polytechnic reserves the right to alter the course, modify the scale of fee, amend any other information or cancel a course with low enrolment.