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Dr Mark Post


Design, Manufacture and Engineering Management

Personal statement

Dr. Mark A Post has been a Lecturer at the University of Strathclyde in the United Kingdom since January 2014, and works with the Space Mechatronic Systems Technology (SMeSTech) Laboratory in the Department of Design, Manufacture and Engineering Management (DMEM). He is principal investigator on two European Commission-funded projects between 2016-2020 on sensor fusion and reconfigurable self-awareness for Space Robotics, which supports the European Space Agency’s future robotic missions.  Dr. Post received his B.A.Sc. in electrical engineering from the University of Toronto in 2004, and his M.Sc. in automated ultrasonic sensing and Ph.D. in space robotics from York University, Canada in 2008 and 2014 respectively. His research focuses on the development of fully autonomous manufacturing systems, mobile robots, and spacecraft.  This includes development of many highly-integrated mechatronic design, sensing, learning, and control technologies that allow intelligent and efficient autonomous operation of robots in harsh environments. He has produced works on many subjects including sensing and modular embedded systems, mechatronic design and testing, autonomous vehicle control, and Bayesian Intelligence. He is an associate editor of the Canadian Aeronautics and Space Journal and has reviewed for several international journals including IEEE Transactions on Industrial Electronics and Mechatronics, the Journal of Spacecraft and Rockets, Advances in Space Research, Sensors, and Acta Astronautica.

He is currently looking for motivated Masters and Ph.D. students in the areas of sensor fusion for space robotics, probabilistic machine learning and reasoning for manufacturing, deep learning for FPGA based real time embedded processing acceleration, dynamic and control for robot and AUV, and structural design for planetary rovers.


Has expertise in:

    Mark Post's experience in research includes machine vision for navigation and recognition, data fusion and actuator control systems, semantic probabilistic learning and reasoning methods, reliable and efficient embedded electronic and power architectures for robots in harsh environments, satellite orbit and attitude control, and manufacturing of structures in both Earth and Space environments.  He has developed feature-based visual mapping algorithms for robotic SLAM and object recognition, nonlinear filters and controllers for deeply-embedded processing and logic, a novel framework for high-reliability real-time distributed autonomous robotics, and innovative applications of probabilistic reasoning for robotic intelligence.

Prizes and awards

Strathclyde Teaching Excellence Award Nomination
Strathclyde Teaching Excellence Award Nomination: Most Innovative Teacher
Strathclyde Teaching Excellence Award Nomination

more prizes and awards


Proof of concept study for small planetary rovers using tensegrity structure on Venus
Post Mark, Li Junquan
16th Reinventing Space Conference, (2018)
A common data fusion framework for space robotics : architecture and data fusion methods
Dominguez Raul, Govindaraj Shashank, Gancet Jeremi, Post Mark, Michalec Romain, Oumer Nassir, Wehbe Bilal, Bianco Alessandro, Fabisch Alexander, Lacroix Simon, De Maio Andrea, Labourey Quentin, Souvannavong Fabrice, Bissonnette Vincent, Smisek Michal, Yan Xiu
International Symposium on Artificial Intelligence, Robotics and Automation in Space Symposia, (2018)
Development of a minaturised forwards looking imager using deep learning for responsive operations
Greenland Steve, Ireland Murray, Kobayashi Chisato, Mendham Peter, Post Mark, White David
4S Symposium 2018, (2018)
Design of a novel wheeled tensegrity robot : a comparison of tensegrity concepts and a prototype for travelling air ducts
Carreño Francisco, Post Mark
Robotics and Biomimetics, (2018)
InFuse data fusion methodology for space robotics, awareness and machine learning
Post Mark, Michalec Romain, Bianco Alessandro, Yan Xiu-Tian, De Maio Andrea, Labourey Quentin, Lacroix Simon, Gancet Jeremi, Govindaraj Shashank, Marinez-Gonazalez Xavier, Dominguez Raul, Wehbe Bilal, Fabich Alexander, Souvannavong Fabrice, Bissonnette Vincent, Smisek Michal, Oumer Nassir W., Triebel Rudolph, Marton Zoltan-Csaba
69th International Astronautical Congress, (2018)
Autonomous navigation with open software platform for field robots
Post Mark A., Bianco Alessandro, Yan Xiu T.
Lecture Notes in Electrical EngineeringLecture Notes in Electrical Engineering, (2017)

more publications


I teach the DM942 Manufacturing Automation and DM952 Intelligent Sensing, Learning, and Reasoning modules at Strathclyde.  I also lecture in DM309 Mechatronics, DM101 Integrating Studies 1, and DM204 Integrating Studies 2.

Two of my most basic philosophies are “Everything is interesting in its own right” and “Anything is possible”. It greatly disturbs me to see students give up on something just because it is “completely boring” or “too hard to understand”. I make a great effort to determine how to present course material in such a way as to make it both interesting and easy to understand, to pass my enthusiasm on to students, andto give students in-class and out-of-class opportunities to play with new science and technology concepts and reach “Eureka” moments of understanding. Memory is most active when new and surprising elements are introduced and every student has a different learning style, so I use a multi-modal learning approach in the classroom incorporating slides and images, video, group activities, real-hardware demonstrations, and visits to laboratories. Learning and memorizing is easier if existing schema in the brain are activated before new information is introduced, so I focus on connecting subjects of study to immediate experiences that students can relate to easily with minimal abstraction. I also balance both summative and formative assessment in my classes to ensure a continuum of learning, and focus on making assessment methods authentic and easy for students to connect to real-world problems by including both memorization of concepts and use of those concepts.

The signature pedagogy of Engineering education is focused on practical applications, but many university programs have considerably more focus on theoretical knowledge rather than its application. When students cannot apply or understand technical concepts, I have found that it is often the link between the theoretical and the practical that is lacking, sometimes termed “Praxis” (Stierer, 2008). To ensure graduates can effectively apply what they have learned, I have frequently championed the cause of experiential education in the university. In a 1995 paper, Coleman has argued for the necessity of ”multi-disciplinary experience and vertical and horizontal integration of skills and teamwork.“ in an engineering program. (R. J. Coleman, "STEP’, 1995). I worked with the York University Rover Team (YURT) to make this student group into an excellent complement to a classroom education, and published results in an IAC conference paper and a journal paper (M.A.Post and R. Lee, “YURT”, Acta Astronautica, 2010). I currently run a Vertically Integrated Projects (VIP) program called Robotic Vehicles for Research and Education (ROVER) so that students can complete real-world robotics projects in a team, and broaden their experiences while obtaining credit for their work.

My philosophies of teaching have centred on these basic concepts:

  1. Provide many points of view to choose from and focus on conceptual simplicity and clarity
  2. Recognize that everyone is different, and structure material to allow for varying skill levels
  3. Ensure that theoretical and practical concepts are connected and associated to familiar ideas
  4. Give everyone a voice, and encourage constructive communication and feedback
  5. Give students freedom to innovate, choose their own path, and have fun with learning

Research interests

Mark Post's research interests focus on technologies to make robots and vehicles fully autonomous for long periods and capable of mobility, comprehensive sensing, and decision-making while handling harsh and rugged environments.  This includes high-reliability and efficient hardware and software architectures for autonomous operation, the design of lightweight and actuated deployable mechatronic structures, and adaptable machine vision and sensor fusion algorithms to give robots a comprehensive understanding of their environment.

Professional activities

16th Reinventing Space Conference
15th Reinventing Space Conference
Control of wave energy converters using machine learning strategies
12'th UK-China Space Workshop
14th International Conference on Informatics in Control, Automation and Robotics (ICINCO)
2018 IEEE Aerospace Conference
Member of programme committee

more professional activities


Understanding Bio-Inspired Robot Propulsion, Maneuvering, and Power ? Hydrodynamic Control & Auton
Xiao, Qing (Principal Investigator) Post, Mark (Co-investigator)
Period 01-Oct-2017 - 30-Sep-2020
Intelligent Collaborative Robotic Manipulation for Advanced Manufacturing and Remanufacturing
Yang, Erfu (Principal Investigator) Post, Mark (Co-investigator)
With Industry 4.0 being currently widely acknowledged as a key driver of industrial advancement, a strong technologic shift has become apparent within industry to move towards both, more intelligence and more autonomy. The fundamental understanding of the strategic application of Industry 4.0 knowledge into practical smart robotic automation is essential to efficiently implement Industry 4.0 in the real world applications, especially for advanced manufacturing and remanufacturing.
Though industrial robots have been widely applied in many sectors including manufacturing and remanufacturing, they are currently facing many emerging challenges arising from (re)manufacturing processes which will have to increasingly deal with the presence of uncertainty, variations caused by the highly customised production, dynamic interactions of humans/other machines including other robots and the need for greater flexibility and intelligence in (re)manufacturing systems. Collaborative concepts in robot-robot and human-robot interaction tend to provide a viable solution to solving these challenges
Period 01-Oct-2018 - 30-Sep-2021
Big Data-Driven Distributed Microseismic Monitoring Method for Hydrofracturing Oil Exploration
Yang, Erfu (Principal Investigator) Durrani, Tariq (Co-investigator) Li, David (Co-investigator) Post, Mark (Co-investigator)
Period 01-Apr-2017 - 31-Mar-2019
Big Data-Driven Distributed Microseismic Monitoring Method for Hydrofracturing Oil Exploration
Yang, Erfu (Principal Investigator) Post, Mark (Co-investigator) Li, David (Co-investigator) Durrani, Tariq (Co-investigator)
This joint-project aims to address the fundamental research challenge related to the development of Big Data-driven distributed microseismic monitoring method for hydrofracturing oil exporation. This research challenge is related to microseismic image information processing and utilization, i.e., how to quickly and efficiently extract and analyze the information of interest for oil detection, tracking its distribution/storage from distributed data/images acquired by a huge number of sensors deployed across the oil field, through either fixed locations or autonomous vehicles platforms, such as unmanned ground vehicle (UGV). To address this challenge faced by the O&G industry, this joint project is focusing on novel Big Data-driven solutions which can integrate distributed data filtering, intelligent analytics and machine learning techniques to offer unique benefits in terms of its ability to bring in data from multiple and distributed sensing sources and provide a full suite of descriptive, predictive and prescriptive analytics.
Period 01-Apr-2017 - 31-Mar-2019
Multi-Purpose CubeSat at the ISS
Post, Mark (Principal Investigator) Vasile, Massimiliano (Co-investigator)
Cubesats are routinely deployed at the ISS but only for classic stand-alone missions, relying on the natural decay of the spacecraft orbit and positive separation from the ISS. Future human exploration missions will require a number of techniques which could be efficiently demonstrated at the ISS with increasing levels of the complexity with a small Cubesat, serving as a multi-purpose platform adaptable for various missions. Among others, the purpose of exterior station inspection will be demonstrated in this project. This study is to define a multi-purpose 8U class Cubesat to be launched from the ISS in a pressurized logistics module and connected to an internal and external docking station for power supply and data transfer (AD[1]).
Period 01-Jan-2016 - 31-May-2016
INFUSE Infusing Data Fusion in Space Robotics (H2020 COMPET-4 OG3)
Post, Mark (Principal Investigator) Vasile, Massimiliano (Co-investigator) Yan, Xiu (Co-investigator)
Period 01-Nov-2016 - 31-Jan-2019

more projects


Design, Manufacture and Engineering Management
James Weir Building

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