Autonomous Systems

Theme leaders:  Dr Alexandru Stancu and Dr Zhengtao Ding

Autonomous Systems is a multidisciplinary research theme within The Faculty of Engineering and Physical Sciences at The University of Manchester with international participation.

Open question: How much information and support must be provided by human to ensure that the robot is able to achieve its goals.


Research Institutes within Faculty of Engineering and Physical Sciences (in alphabetical order):

Aerospace Research Institute

Dalton Nuclear Institute


Schools within Faculty of Engineering and Physical Sciences (in alphabetical order):

School of Computer Science:

Prof Timothy Cootes

Dr Neil Thacker

Dr Renate Schmidt

Dr Stephen Pettifer

School of Electrical and Electronic Engineering:

Dr Zhengtao Ding

Prof Andrew Forsyth

Mr Peter M. Green

Dr Peter R. Green

Prof Barry Lennox

Dr Mohamed Mustafa

Dr Salvador Pacheco

Prof Sandy Smith

Dr Alexandru Stancu

Dr Rebecca Todd

Prof Hong Wang

Dr Chunyan Wang

Dr Simon Watson

School of Materials:

Dr Clara Frias

Dr Matthieu Gresil

Dr Enrique Jimenez-Melero

Prof Prasad Potluri

Prof Constantinos Soutis

School of Mechanical, Aerospace and Civil Engineering:

Dr William Crowther

Dr Antonino Filippone

Dr Bilal Kaddouh

Dr Alistair Revell

Members from other universities (in alphabetical order):

Dr Joaquim Blesa - Polytechnic University of Catalonia, Barcelona, Spain

Dr Bogdan Codres - “Dunarea de Jos” University of Galati, Romania

Dr Jörg Conradt - Technical University of Munich, Germany

Prof Victor Giurgiutiu - University of South Carolina, USA

Prof Luc Jaulin - ENSTA Bretagne, France

Dr Lino Marques - Institute of Systems and Robotics, University of Coimbra, Portugal

Dr Lyudmila Mihaylova - University of Sheffield, UK

Prof Vicenç Puig - Polytechnic University of Catalonia, Barcelona, Spain

Prof Gheorghe Puscasu - “Dunarea de Jos” University of Galati, Romania

Prof Joseba Quevedo - Polytechnic University of Catalonia, Barcelona, Spain

Prof Nacim Ramdani - University of Orléans, France

Dr Thomas Schmickl - Artificial Life Laboratory, University of Graz, Austria

Dr Razvan Solea - “Dunarea de Jos” University of Galati, Romania

Dr Jürgen Stradner - Artificial Life Laboratory, University of Graz

Dr Lingyu Yu - University of South Carolina, USA

Industrial partners (in alphabetical order):

MBDA Systems Ltd, UK

National Nuclear Laboratory, UK

Robosoft, France

Sellafield Ltd, UK

SpaceTech GmbH, Germany

Teamnet Group, Romania

PhD students:

Mr Eduard Codres

Mr Zhenhong Li

Mr Mario Martinez Guerrero

Mr Bradley Robertson Welsh

Mr Bowen Peng

Mr Jingduo Tian

Mr Ishak Tnunay

Miss Alma Rebeca Velasco Olmos

Mr Jiameng Xue

Mr Xiaomo Yan

This theme has the strategic aim of developing innovative scientific methods that lead to technologies requiring minimal human intervention. Research partnerships have been established with BAE Systems, National Nuclear Laboratory, North West Aerospace Alliance, Rolls-Royce, and Roke Manor Research. Achievements include intelligent agent-based energy-management and autonomous mission re-planning, developed through participation in the Integrated Electrical Power Networks Evaluation Facility (IEPNEF), and autonomous robots being developed for nuclear decommissioning applications through the £20m Dalton Cumbrian Facility, which is now a National Nuclear User Facility.  

Autonomous systems are used for a variety of purposes including performing remote tasks in hazardous environments and remote sensing. Autonomous systems need to interact with an unknown, unstructured environment and need to sense and decide upon unexpected events that they encounter while performing their planned tasks. Autonomous Systems typically manifest themselves as mobile robotic platforms which operate in one of following domains:


Unmanned Aerial Vehicles (UAVs)

UAVs are increasingly becoming popular in reconnaissance, surveillance and exploration applications. UAVs are flying vehicles that are automatically controlled to perform a certain set of tasks independent of user intervention. Autonomy adds a layer of software intelligence allowing the vehicle to take cognitive decisions based on its situational awareness. Examples of common UAV platforms include unmanned small helicopters, unmanned quad-rotor vehicles and unmanned fixed wing aeroplanes.


Unmanned Underwater Vehicles (UUVs)

UUVs are vehicles which operate underwater with minimal or no interaction with a base ship or with the shore. Applications include undersea exploration, the detection of pollution in rivers, exploration of ice-shelves in Antartica and the mapping of large scale, liquid-based industrial processes.


Unmanned Ground Vehicles (UGVs)

UGVs operate on the ground and drive without operator assistance. Such ground vehicles can interact with the environment and manipulate objects as they can exert considerable forces on the environment. Burrowing vehicles, which support the investigation of subsurface phenomena, can also be considered a sub-set of UGVs.


Common issues across all of the above categories include propulsion, control and sensing, supporting hardware and software designs, and autonomy algorithms and cognitive processes. Higher level strategies for surveillance, mapping and exploration are also important, as are techniques that combine data from a variety of sensors to enable a detailed description of an environment or phenomenon to be constructed. This theme is about creating supporting technologies for the above types of vehicles.

Researchers in the Autonomous Systems Theme develop autonomous systems for real-world industrial applications. We work with unmanned vehicles that operate in all the above three domains. We explore new sensing technologies, novel vehicle platforms, new control strategies, new cognitive algorithms, power management and optimisation, and methods and tools for perception, abstraction, path-planning and decision making.

Please enjoy some of our robotic demos:

Demo 1 - Guaranteed SLAM and Probabilistic SLAM running in parallel (Simultaneous Localisation and Mapping). Indoor experiment, no GPS available  

Demo 2 - Probabilistic SLAM (Simultaneous Localisation and Mapping) and Shape Detection. Indoor experiment, no GPS available 

Demo 3 - Fault tolerant squad of autonomous robots mapping an industrial environment

Demo 4 - Consensus control for a squad of autonomous robots in an industrial environment

Demo 5 - Two autonomous robots in a simulated environment

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