[NP-SDRE] Specialist Diploma in Robotics Engineering (SDRE)

Offered by School of Engineering

Specialist Diploma

About Course
Course Structure
Entry Requirements
Financial Matters
Course Schedule

About Course

Course Objectives

The course prepares trainees to gain in-demand skills and expertise in robotics engineering for them to be able to design an intelligent robot that can see, speak, “think”, and perform simple tasks traditionally carried out by a human. Robotics engineering can play an important role in various industries to augment workforce capabilities, from manufacturing & logistics to environment, and hospitality & healthcare to construction.

Course Description

The SDRE consists of two post-diploma certificates (PDCs), with a total of 7 modules:
•   Robotics with Python
•   Robotics with C++
•   Robot Operating System (ROS) & Robotics
•   Autonomous Robot Navigation
•   Machine Learning for Robotics
•   Computer Vision & Deep Learning for Robotics
•   Robotics Real-world Project

Trainer's Profile

Hui Tin Fat

Hui Tin Fat holds a BSc in Electronic Engineering and an MSc in Telematics, both from the University of Essex, UK. With over 30 years of experience in the design and development of microcontroller-based embedded systems, Tin Fat has specialised in robotics and automation systems. In the past five years, Tin Fat has focused on ROS-based robotic systems. He has also been actively involved in consultancy and industrial collaboration projects. These include supplying 20 Advanced Mobile Robot Kits to ITE West, enhancing point-of-sale systems for a local company, developing a canopy cleaning robot for a smart campus, creating a multipurpose disinfection robot for a polyclinic, and designing plant-health monitoring robots for NParks. Additionally, Tin Fat has developed mobile apps for campus autonomous bus shuttle services and construction robots for local SMEs.

Tin Fat’s professional achievements include being a nominee for the National Youth Award, receiving the Singapore Award for Excellence from the Singapore Totalisator Board, the National Day Commendation Award, and the Polytechnic Teaching Award.

Tin Fat’s research contributions are published in renowned journals. Notable publications include "Introducing a Healthcare-Assistive Robot in Primary Care: A Preliminary Questionnaire Survey" in Frontiers in Robotics and AI, and "Early Detection of Infestation by Mustard Aphid, Vegetable Thrips, and Two-Spotted Spider Mite in Bok Choy with Deep Neural Network (DNN) Classification Model Using Hyperspectral Imaging Data" in Computers and Electronics in Agriculture.

Currently, Tin Fat is the module leader of Embedded Robotics, where he imparts knowledge and skills in ROS-based navigation robots to students in the PET Electronic & Computer Engineering course.


Edwin Ho Hui Leong

Edwin Ho holds a Bachelor's and a Master’s degree in Mechanical and Production Engineering from Nanyang Technological University.

Edwin's research passion centres around industrial robots, autonomous systems, and computer vision, leading to the development of various robotic applications. Notably, he served as the principal investigator for a Decentralised GAP Funded project.

Since 2010, he has been a lecturer at Ngee Ann Polytechnic's School of Engineering, teaching final year students about Unmanned Systems and industrial Robotics. Edwin also leads the Robotic Research and Innovation Centre, leveraging his expertise from prior roles focusing on Machine Design, Automation, and advanced mechatronic systems where precision motion control and nanometric actuated motions are key requirements. Edwin also teaches “ROS for industrial Robots” to short course CET learners and is a module leader for “Robot Operating System and Robot Applications” in Specialist Diploma for Robotic Engineering.

Course Structure

TPG course reference No.

TGS-2021005342

Specialist Diploma in Robotics Engineering

Post-Diploma Certificate in Intelligent Autonomous Robotics
Autonomous Robot Navigation (NP-013329)
Participants will gain essential technical skills to develop and deploy autonomous mobile robots for various applications. Topics that will be covered are: Hardware for Robot Navigation System, TF, URDF, Simultaneous Localization and Mapping (SLAM) in ROS Navigation Stack, Mapping, Localization, Path Planning, Path Execution, Obstacle Avoidance, Waypoint Management, Odometry Kinematics, and configuration and programming of real robots.
Computer Vision & Deep Learning For Robotics (NP-013331)
Students will acquire computer vision and deep learning skills to solve real-word problems. The topics in this module are: Overview of Computer Vision, OpenCV Functions for Image Processing and Object Detection, Convolutional Neural Networks (CNN), Image Classification using Deep Learning, Building CNN Models with Tensorflow 2, Classifying images using Keras; Transfer Learning, Object Detection using Deep Learning, Object Detection Algorithms including SSD, YOLO and Faster R-CNN, Real-Time Object Detection Application with Tensorflow 2, and Case Study: Person Re-Identification.
Machine Learning For Robotics (NP-013330)
This Machine Learning module offers an in-depth overview of Machine Learning topics that include: Working with Real Data, Developing Algorithms using Supervised, Unsupervised and Reinforcement Learning, Regression, Classification, Time Series Modelling, Using State-of-the-art Machine Learning Frameworks to Solve Problems Efficiently.
Robotics Real-world Project (NP-013332)
This capstone project allows trainees to integrate the acquired skills into a robot product. The project involves the development of key modules of a concierge robot and system integration.
Post-Diploma Certificate in Robotics Programming Fundamentals
Robot Operating System (ROS) & Robotics (NP-013328)
This module equips trainees with foundational knowledge and skills in ROS for robotics. The topics trainees will learn include: Overview of ROS Ecosystem, Linux Basics, ROS Installation and Setup, Catkin Workspace, ROS Master, Packages, Nodes, Topics, Messages, Publishers, Subscribers, Services, Custom Msg and Srv, Actions, Debugging and Visualization Tools in ROS, Parameters, OOP with ROS with Python and C++, Launch files, Bags, and Introduction to ROS2.
Robotics with C++ (NP-013327)
Participants will acquire C++ programming skills for robotics engineering. The topics in this module are C++ Basics, Type Conversion, Reference, Pointers, Preprocessor Statements, Dynamic Memory, Fundamentals of Object-Oriented Programming, Inheritance, Polymorphism, Exception Handling, I/O and Streams, Standard Template Library, Function Template, Class Template, and Application of C++ in Robotics.
Robotics with Python (NP-013326)
Students will learn the Python programming skills essential for robotics engineering. The topics covered include: Essentials of Python Programming, Data Structures in Python, Object Oriented Programming, Comprehension, Lambda, Generators, Decorators, File Handling, Exception Handling, Modules, Packages, and Applying Python in Robotics Projects.

Entry Requirements

Condition 1

Highest qualification

Local polytechnic diploma in any engineering discipline.
or

Condition 2

Highest qualification

University Degree in any engineering discipline where the medium of instruction is English.

Financial matters

Course fees payable (incl. GST & excl. supplementary fee)

Description Post-Diploma Certificate in Robotics Programming Fundamentals Post-Diploma Certificate in Intelligent Autonomous Robotics Total course fee
Full Course fee $2,825.28 $2,825.28 $5,650.56
PR Sponsored by SME $294.19 $294.19 $588.38
Singapore Citizen Sponsored by SME $294.19 $294.19 $588.38
Singapore Citizen Aged 40 & Above $294.19 $294.19 $588.38
Singapore Citizen Aged Below 40 $423.79 $423.79 $847.58
Singapore PR $1,130.11 $1,130.11 $2,260.22
Long-Term Visit Pass Plus $2,825.28 $2,825.28 $5,650.56

GST rate

The course fees payable above are inclusive of 9% GST rate.

Payment option

The first payment needs to be made after accepting the offer.

Allowed payment by

The course fee allows to be paid by:
Post-Secondary Education Account (Adhoc withdrawal form);
Post-Secondary Education Account (Standing order form);
SkillsFuture Credits (SFC);
Credit card (e-payment);
Debit card (e-payment);
PayNow (e-payment).

Nett Supplementary Fees Payable

  • GPA Insurance Fee S$2.13,subject to GST,fees payable S$2.32 Allow payment by Post-Secondary Education Account (Adhoc withdrawal form); Allow payment by Post-Secondary Education Account (Standing order form)
  • Other Fees S$7.50,subject to GST,fees payable S$8.18 Allow payment by Post-Secondary Education Account (Adhoc withdrawal form); Allow payment by Post-Secondary Education Account (Standing order form)

Refund and withdrawal policy

  • Please note that a 100% refund will be available if the withdrawal request is submitted more than or equal to 14 days before the course start date.
  • Please note that a 50% refund will be available if the withdrawal request is submitted less than 14 days before the course start date.
  • Please note that no refund will be available if the withdrawal request is submitted on or after the course start date.

Course 
Schedule

Class Day(s): Mon, Tue, Thu, Fri
Time: Evening (from 6:30pm to 10.00pm)
Delivery Mode: Face-to-face & Home-based Learning (Async & Sync)