School of Physics, Engineering and Technology
Senior Lecturer (Associate Professor) in Robotics and Autonomous Systems
Tel: +44 (0)1904 32 2393
Lab: +44 (0)1904 32 2315
Research Area: Robotics and Autonomous Systems
Research Expertise: Robotics and Mechatronics, Autonomous Systems, Sensing and Control
Mark A. Post received his B.A.Sc. in electrical engineering from the University of Toronto in 2004, and his M.Sc. in ultrasonic material analysis and Ph.D. in space robotics from York University in Canada in 2008 and 2014 respectively. From 2014-2018 he worked on novel autonomous manufacturing, agricultural robotics, and space robotics technologies including mobility, vision, and sensor fusion in the Space Mechatronic Systems Technology Laboratory at the University of Strathclyde. He joined the School of Physics, Engineering and Technology at York in 2019 and focuses on applying both space and terrestrial robotics technologies to challenges in comprehensive sensing, artificial intelligence, self-awareness, and bio-inspired adaptable structures for robotics. He has reviewed for several international journals including IEEE Trans. on Industrial Electronics and Mechatronics, Journal of Spacecraft and Rockets, Advances in Space Research, Sensors, and Acta Astronautica and so on. Mark was made a Senior Lecturer in 2022
Publications information is available via the York Research Database
My research interests focus on technologies to make robots and vehicles fully autonomous for long periods and capable of mobility, sensing, and adaptability in harsh and distant environments. This includes self-awareness and self-configurability by robust probabilistic reasoning on semantic information, control of lightweight and reconfigurable mechatronic structures, and adaptable machine vision and sensor fusion algorithms to give robots a comprehensive understanding of their environment.
3D-RSS: a 3D radioactive scanning system
Radiation detection provides a crucial component of societally-important applications such as homeland security and nuclear decommissioning. This project applies extensive research by the Nuclear Physics group into scintillator-based detector technology focussing on employment of compact and low cost silicon photomultipliers (SiPMs) for scintillation light collection, with modular robotics and SLAM sensory technology employed by the Intelligent Systems and Robotics group. The objectives of this project are to fuse a directional planar scintillator with LIDAR, camera, and inertial measurement sensors on a modular robotic system to achieve automated three-dimensional localization and mapping of radiation sources identified within volumetric environments.
RoboFish: Autonomous Biomimetic Robot-fish for Offshore Wind Farm Inspection (EPSRC, Supergen ORE Hub, 2019-2021)
RoboFish is an autonomous, bio-mimetic AUV capable of navigation about dense and moving underwater structures for the propose of continuously and autonomously locating and monitoring structural damage to Offshore Renewable Energy infrastructure such as floating wind farms. The project is funded by the Supergen ORE Hub, and partners in this project are University of Strathclyde, PicSea Ltd, East Coast Oil and Gas Engineering Ltd.
Control methods for flexible and bio-inspired superlight tensegrity rovers (internal funding 2019-2022)
Autonomous Robotics vehicles for planetary exploration must be responsive, energy efficient, lightweight for transport, and mechanically robust. To accomplish these goals, a small rover platform driven by the need for light weight, simplicity and reconfigurability is being developed with a minimalist mechanical structure and a flexible software design model to facilitate additions and multiple use cases. The advantages of this platform are resilience and transportability due to the low mass thin structural members of the tensegrity spine chassis, and the combined adaptability of wheeled and full-body movement. The use of flexible and distributed structures allows the rover to better adapt physically to complex and varied terrains such as those encountered on Martian slopes. We have a tensegrity rover prototype that students can work on by testing out new actuators, control methods, and payload tasks, in addition to the possibility of students testing out new forms of flexible and tensegrity robots.
MOSAR - MOdular Satellite Assembly and Reconfiguration
MOSAR is a Horizon 2020 funded project to develop a sound technology demonstrator of on-orbit modular satellite reconfiguration relying on robotic capabilities and exploiting the outcomes of previous Space Robotics SRC building blocks. MOSAR shall elaborate and refine the concept of Modular Spacecraft, identify and recommend standards and design the ground and space infrastructure elements that will enable its realisation and sustain its progressive deployment and economical exploitation.
Thickness AI (Innovate UK 2019-2021)
This project led by Macro Engineering & Technology Inc. (Canada) with with Peacock Technology Limited, University of York and University of Strathclyde (UK) titled “Development of Thickness Control using AI Controls for Blown Film Air Ring”. Develop an auto-profile airing system controlled by Artificial Intelligent software designed to improve gauge uniformity in blown film extrusion equipment
InFuse: Infusing Sensor Fusion Into Space Robotics
InFuse is a European Horizon 2020 funded project in which a consortium of expert companies and organisations have developed a novel Common Data Fusion Framework (CDFF) for the Space Robotic Technologies Strategic Research Cluster (SRC).
Standard Interface for Robotic Manipulation of Payloads in Future Space Missions (SIROM)
SIROM is another project in the Horizon 2020 Space Robotics SRC in which a standard mechanical, electrical, and thermal interface between robotic space systems has been developed.
The Agribot: Autonomous, repeatable sensing for improving crop yields and farm field monitoring
James White 2019-2023 Topic: Self-Organising reconfigurable cellular robots with semantically aware elements.
Tianyuan Wang 2019-2023 Topic: Design of an Autonomous Topological Modular Wheeled Tensegrity Robot
Yunlong Lian 2020-2024 Topic: CPG-based dynamic locomotion learning fo a bionic quadruped robot
Haowen Liu 2021-2025 Topic: Machine Learning for Controlling Bio-Inspired Robots on Complex Terrains
Hanyang Zhong 2022-2026 Topic: Bio-inspired miniaturized light weight autonomous underwater vehicles and Manipulators for Sea and Ocean Environments
MSC by Research students:
Qi He 2019-2021 Topic: Robotics and Autonomous Systems —— Bio-Inspired Robotics
Positions are currently available for PhD students and MSc by Research students
I coordinate the University of York's Intelligent Robotics MSc programme and lead the Control and Robotics Teaching Stream in the School of Physics, Engineering and Technology. My approach to teaching emphasizes experiential education and focuses on helping students build a strong theoretical understanding of science and technology in the context of Engineering challenges, and then applying this understanding to solve practical problems in the physical world. I also incorporate both practical experience and novel research into my teaching and try to help students find what they are most interested in throughout their studies. Most of the modules I teach follow a 'flipped classroom' format where lectures are pre-recorded and other sessions focus on discussion, exercises, and most importantly hands-on work building, implementing and creating in the laboratory. The modules I teach include