Thursday, 28 May 2020

UPEIFA Merit Award for Scholarly Achievements

Dr. Ngo recently received the UPEIFA Merit Award for Scholarly Achievement. This prestigious award was nominated and selected by the university colleagues.

Friday, 20 March 2020

A journal paper published on Electronics

Tung Le (former PhD student of the MoreLab) and Dr. Trung Dung Ngo recently published a paper "Virtual pheromone based network flow control for modular robotic systems" on Electronics. This paper can be viewed and downloaded at:

Monday, 2 December 2019

NSERC CREATE iMERIT - the large and longest NSERC fund.

Together with colleagues from Dalhousie University, University of New Brunswick, and Memorial University of Newfoundland, the Morelab is the unique representative of University of Prince Edward Island in the NSERC CREATE - iMerit training program, one of the largest NSERC funding in Canada. Please visit the website of our iMerit program for more info:

Wednesday, 20 November 2019

Two papers accepted at IEEE SII 2020

We do have two papers accepted at the IEEE International Symposium on System Integration, Hawaii, January 2020. Citations can be found below. 
  • Gradient-based Routing Protocol for Modular Robotic Systems, Tung Van Le, Van Anh Ho, Trung Dung Ngo, IEEE International Symposium on System Integration, Hawaii, January 2020.
  • Adaptive Hierarchical Distributed Control with Cooperative Task Allocation for Robot Swarms, Pham Duy Hung, Hung Manh La, and Trung Dung Ngo, EEE International Symposium on System Integration, Hawaii, January 2020.

Wednesday, 5 June 2019

Special issue on Robotic Co-workers: Psychological and Cognitive Safety in Human-robot Interactive Social Environments - IEEE Transactions on Cognitive and Development Systems

*Important Dates*
31 December 2019 – Deadline for manuscript submission
15 Apr 2020 – Notification of authors
15 May 2020 – Deadline for revised manuscripts
15 July 2020 – Final version

Guest Editors*

Dr. Trung Dung Ngo
University of Prince Edward Island, Canada,

Dr. Rachid Alami
LAAS-CNRS, University of Toulouse, France

Dr. Takayuki Kanda
Kyoto University, Japan

Dr. Goldie Nejat
University of Toronto, Canada

Dr. Yongsheng Ou
SIAT, Chinese Academy of Science, China

*Aim and Scope*
In the vision of a cyber-society, humans and robots will closely collaborate to perform given tasks. Robots will automate mundane tasks and let humans focus on higher-order jobs requiring more cognitive skills. In this trend, professional and personal service robots are enabling assistive technologies in human-robot shared workspaces. However, the first and the most challenging issue with respect to deploying developmental and cognitive robots in human populated environments is how to guarantee human physical and cognitive safety in human-robot shared workspaces. Physical safety is about how to maintain a minimum physical distance between robots and humans, which is obviously necessary to deploy autonomous robots in human populated environments, while cognitive safety implies that robots should not cause stress and discomfort to humans when working with or around them. Human risks and their inconveniences when working in an interactive social environment essentially come from unavoidable situations due to robot malfunctioning operations caused by either misunderstanding and misinterpreting information extracted from sensing and perception or failures of path planning and motion control. Furthermore, humans may feel uncomfortable as well as fearful and stressful towards collaborative robots as such robots don’t behave in the natural way of humans with respect to their social situations, contexts, and cultures. It is important to find out a methodological approach for incorporating social signals, cues, and norms into developmental perception, cognitive reasoning and motion planning of the robot control architecture so that the robot is capable of securing human psychological and cognitive safety when interacting and collaborating with humans to perform tasks in human-robot shared workspaces.

The Special Issue aims to address challenges and methodologies of how to deal with psychological and cognitive safety in order to accelerate deployment and adoption of developmental and cognitive robots into human-robot shared workspaces. The ultimate goals of this special issue are to (1) to address the state-of-the-art research (2) and to generate an avenue for researchers to disseminate their recent research findings in the perspective of psychological and cognitive safety in human-robot shared workplaces.
This special issue targets on all aspects of guaranteeing psychological and cognitive safety in human-robot interactive social environments with, but not limited to, the following topics: 

Current state-of-the-art: future perspective of developmental and cognitive robots with concerns of ethics and rules for human psychological and cognitive safety in human-robot shared workspaces.
Perception for psychological and cognitive safety: capacity and roles of human face and body detection and tracking, human gestures and posture recognition, social cues and signal detection and identification, human-object interaction and human group interaction detection and tracking in satisfying psychological and cognitive safety. 
Cognitive reasoning, motion planning and control: methodological development of human aware robot navigation, collaborative task performances in dynamic social environments with concerns of psychological and cognitive safety.
Machine learning for developmental and cognitive robots: using learning by demonstration, reinforcement learning, deep learning, and hierarchical learning to enhance psychological and cognitive safety in human-robot shared workplaces.
Ergonomic studies of developmental and cognitive robots: developmental and cognitive factors and benchmarks, evaluation methods, objective and subjective measurement metrics, experiments and validation methods for psychological and cognitive safety.
Applications domains: concerns of psychological and cognitive safety when working with developmental and cognitive robots in public places, light industry, digital manufacturing, and transformed manufacturing.

*Submission Guideline*
Manuscripts should be prepared according to the “Information for Authors” of the journal found at and submissions should be done through the IEEE TCDS Manuscript center: and please select the category “SI: Psychological and Cognitive Safety”.

Monday, 22 April 2019

A paper to be appeared on IEEE Transactions on Cybernetics

We are happy that our latest research result has been accepted to appear on IEEE Transactions on Cybernetics.

"Hierarchical Distributed Control for Global Network Integrity Preservation in Multi-Robot Systems", Pham Duy Hung, Tran Quang Vinh, and Trung Dung Ngo, IEEE Transaction on Cybernetics (pre-print). 

A new special issue on "Modern Mechatronics and Automation - An Open-Source Approach"

I am organizing a new special issue on  "Modern Mechatronics and Automation - An Open-Source Approach". Please submit your original paper to it.

Nowadays, we can see modern mechatronic systems and automation everywhere, from industrial manufacturing to home automation. Using open-source hardware and software to rapidly prototype and develop mechatronic and automated systems has been well recognized by technological developers. Open-source electronic platforms such as Arduino, Raspberry PI boards and its compatible devices become a part of teaching and research activities at universities. The trend of shared source codes and documentation on the web-based software platforms, e.g. Github, allowing professionals and amateurs to access and collaborate their intellectual works has been promoted and implemented at not only open-source communities but also the leading technological corporations. Ethical laws on open-source hardware and software have been frequently consolidated along the incredible growth of the open-source world. Indeed, technological and social impacts of open-source hardware and software in mechatronics and automation are not deniable.

The primary aim of this Special Issue is to gather the most recent methodologies, technologies, and applications of open-source hardware and software in modern mechatronics and automation. We invite all papers with novel contributions in principles, development and applications of open-source hardware and software with, but not limited to, the following topics:

·      Current state of the art of open-source hardware and software used in mechatronics and automation.
·      Use open-source hardware and software in prototyping and development of mechatronics and automation.
·      Impacts of open-source approach on development and applications of mechatronic systems.
·      Ethical laws for open-source hardware and software in mechatronics and automation.  
·      Methodologies of using open-source platforms in research and education.

-       Open-source hardware
-       Open-source software
-       Open-source drivers
-       Free operating systems
-       Modern mechatronics
-       Internet of Things (IoT)
-       Cyber-physical systems (CPS)
-       Robotics
-       Do-it-yourself (DIY)
-       Rapid prototyping
-       Rapid development

A paper appeared on The Visual Computer

Our latest paper "Face detection and tracking using hybrid margin-based ROI techniques" appeared on the Visual Computer.

Face detection and tracking using hybrid margin-based ROI techniques", Bacha Rehman, Wee Hong Ong, Abby Chee Hong Tan, and Trung Dung Ngo (pre-print).

Thursday, 13 September 2018

Open positions at the MoreLab

Postdoctoral fellowship, PhD and Master scholarship are available at the, Canada

Position 1: High-level Perception for Human-robot Interaction and Collaboration
Good knowledge in computer vision/robot vision is required. Practical experience in sensor fusion and data association is plus.

Position 2: Socially Capable Mobile Robot Navigation
Good knowledge in robot perception, path planning, motion planning and control is required. A strong background in algorithms is plus. Hands-on skills of system integration are highly expected.

Position 3: Deep Reinforcement Learning for Socially aware Robot Navigation
Fundamental knowledge in machine learning for robotics is required. Practical experience of applied AI in robotics and autonomous systems is highly expected.

Position 4: Multi-robot Systems/Swarm Robotics
Solid background in Math and Control Theory is required. Algorithmic thinking and programming skills are required for this project. 

You can find demonstrations of our research projects at:

PhD and Master applicants with background in Engineering and Computer Science (Robotics, Control Engineering, Robot Vision and AI) are welcome. Good knowledge in Math
and practical experience in Computer Programming are required. Hands-on skills in ROS and Matlab are highly expected.

Admission requirements for PhD and Master students: English score (IELTS >= 7.0 or TOELF>= 100) and high GPA (>75%) of your degree(s). 

Feel free to contact the lab director ( for more information. Please send your CV, degrees and transcripts, samples of your research work along with a research statement to express your interests in a position.