Communication & Networks

Academic Contact: Ian Robertson
Academic Staff: Dr Andrew Jackson, Dr Andrew Kemp, Dr Chris Trayner, Dr David Cowell, Dr Des McLernon, Dr Nicolas Salazar Sutil, Dr Nutapong Somjit, Dr Syed Ali Raza Zaidi, Professor Ian Robertson, Tim Amsdon, Viktor Doychinov

Leeds has an extensive range of relevant expertise in communication and networks that is being applied to new challenges in robotics and autonomous systems. Wireless communications are a key enabling technology for basic remote control of robotics, while 5G systems offer exciting prospects for cloud robotics, swarms and cyber physical systems. As an underpinning technology, our expertise is being applied in all the key application areas of Robotics at Leeds. We are pursuing an exceptionally wide range of robotic communications research, including:

  • Design and Implementation of communication protocols for future robotics and autonomous systems
  • Design and Implementation of robotic systems to enable autonomous deployment of future communication networks
  • Localisation and control for robotics and autonomous systems
  • Energy harvesting and wireless power transfer for mobile robots
  • Microwave design for high frequency (mm-Wave and beyond) communication and Cloud Robotics
  • Mobile Edge computing for robotics and machine-to-machine (M2M) communication systems
  • Design and implementation of large scale internet-of-things (IoT) networks
  • Signal processing for Machine Learning
  • Networked control of multi-agent systems.

As well as pursuing communications research that is world-class in its own right, we have a wide range of research collaborations with colleagues at Leeds in the areas of field robotics, robotic surgery and rehabilitation robotics. The major current funded projects that we contribute to include:

  • Balancing the Impact of City Infrastructure Engineering on Natural systems using Robots, EPSRC Grand Challenge
  • Pervasive Sensing for Buried Pipes, EPSRC Programme Grant. This project, led by the University of Sheffield, is researching into advanced robotic swarms that can inspect and repair the underground pipe network (
  • Hospital Environment Control, Optimisation and Infection Risk Assessment (HECOIRA). This EPSRC project is doing novel work in developing sensor network technology for Air Quality monitoring (

Millimetre-Wave Communications

This work is particularly focused on 5G and ultra-wideband communications in the millimetre-wave bands (e.g. the 26-28 GHz band for 5G and the 57-63 GHz unlicensed band) since it provides the bandwidth needed for precise positioning of robots to allow cloud connectivity, coordination of movement and sharing of data (relaying and aggregation of imaging and sensing information). The National Facility includes the Wireless Communications Test Bed which allows Gigabit/s testing of transmitters, receivers and individual subsystems to 110 GHz. In addition, the Pollard Institute has a high frequency measurements laboratory, sponsored by Keysight Technologies that houses a suite of vector network analysers that permit the precision characterisation of devices, components and materials at frequencies up to 1.1 THz.

Communications Networks

This area includes research on intelligent, adaptive, self-organising wired-wireless networked infrastructures; modelling of 5G networks, Internet of Things networks, vehicular and robotic networks, storage and media (in particular video) networks and end-to-end quality-of-service in current and future access networks and core networks. We are also researching into PHY layer security, M2M comms/caching in heterogeneous networks, SDNs, distributed sensing, stochastic geometry, multi-packet reception, through the wall radar, drone/UAV small-cell communications and spectrum sensing for cognitive radio.

Signal processing

This work includes mobility diversity algorithms and RF energy harvesting. There are many applications in which a mobile robot, with limited energy resources (e.g. battery powered), must perform some task (e.g. environmental sensing) and then transmit data back to a base station. However, the robot will often experience small-scale fading of the wireless communication channel, and so it must seek a position (from which to transmit) that has a high wireless channel gain – thus minimising the amount of (electrical) energy needed to send the data. This will also deplete the robots stored energy resources through the (mechanical) energy expended in the process of searching for the best location to transmit from. The research involves developing mathematical algorithms based on “mobility diversity” that optimise the robot’s trajectory so as to minimise the overall energy (mechanical plus electrical) consumption. A demonstrator test bed using iRobot Create platform is being developed to apply these techniques along with intelligent radio frequency energy harvesting.

Localisation and Wireless Sensor Networks

Many robotics applications need knowledge of position and in many cases specific communication protocol solutions that are reliable, low power and efficient.  For example, to provide knowledge of position typically requires increased data traffic across the robotic network which may already be overloaded with sensing and control data.  Our work covers all these areas e.g. how to relieve congestion across IoT networks, routing of data and the provision of algorithms to utilize available information to generate the best localization solution. This includes positioning systems for wireless devices, along with the analysis and improvement of localization techniques using Time of Arrival (ToA) and Received Signal Strength (RSS). We are studying energy efficiency and QoS in WSNs using optimal routing algorithms and investigating geographic routing performance under various network distributions and erroneous localization, developing reliable, efficient location based routing protocols under realistic assumptions. Professor Andy Kemp is leading a team of sensor network personnel in the HECOIRA project. This is doing novel work in developing sensor network technology for Air Quality monitoring.

Pipeline Inspection

The technical barriers to using wireless communications for tetherless robotic pipeline inspection include precise determination of location, the high signal attenuation due to metal permeability, multipath propagation, loss due to high pressure gas, gas flow, battery life, along with safety and regulatory issues. An optimum solution is required that can overcome these problems and provide reliable communications with sufficient bandwidth and range to meet inspection requirements, particularly with the aim of inspecting bends and junctions that are not currently pig-able. The robots will need high bandwidth because of video and high resolution images and this will necessitate wireless carrier frequencies in the GHz range.


A. M. Hayajneh, S. A. R. Zaidi, D. C. McLernon, M. Di Renzo and M. Ghogho, “Performance Analysis of UAV Enabled Disaster Recovery Networks: A Stochastic Geometric Framework Based on Cluster Processes,” in IEEE Access, vol. 6, pp. 26215-26230, 2018. doi: 10.1109/ACCESS.2018.2835638

D. B. Licea, D. McLernon, M. Ghogho (2017) “Mobile Robot Path Planners with Memory for Mobility Diversity Algorithms”, IEEE Transactions on Robotics, Volume: 33, Issue: 2. doi: 10.1109/TRO.2016.2636848

W. Li, D. Mclernon, J. Lei, M. Ghogho, S. A. R. Zaidi and H. Hui, “Cryptographic Primitives and Design Frameworks of Physical Layer Encryption for Wireless Communications,” in IEEE Access, vol. 7, pp. 63660-63673, 2019. doi: 10.1109/ACCESS.2019.2914720

W. Li, D. Mclernon, K. Wong, S. Wang, J. Lei and S. A. R. Zaidi, “Asymmetric Physical Layer Encryption for Wireless Communications,” in IEEE Access, vol. 7, pp. 46959-46967, 2019. doi: 10.1109/ACCESS.2019.2909298

H. Kharrufa, H. Al-Kashoash and A. H. Kemp, “A Game Theoretic Optimization of RPL for Mobile Internet of Things Applications,” in IEEE Sensors Journal, vol. 18, no. 6, pp. 2520-2530, 15 March15, 2018. doi: 10.1109/JSEN.2018.2794762

H. A. A. Al-Kashoash, H. M. Amer, L. Mihaylova and A. H. Kemp, “Optimization-Based Hybrid Congestion Alleviation for 6LoWPAN Networks,” in IEEE Internet of Things Journal, vol. 4, no. 6, pp. 2070-2081, Dec. 2017. doi: 10.1109/JIOT.2017.2754918

N. Chudpooti, N. Duangrit, P. Akkaraekthalin, I. D. Robertson and N. Somjit, “220-320 GHz Hemispherical Lens Antennas Using Digital Light Processed Photopolymers,” in IEEE Access, vol. 7, pp. 12283-12290, 2019. doi: 10.1109/ACCESS.2019.2893230

B. T. Malik, V. Doychinov and I. D. Robertson, “Compact broadband electronically controllable SIW phase shifter for 5G phased array antennas,” 12th European Conference on Antennas and Propagation (EuCAP 2018), London, 2018, pp. 1-5. doi: 10.1049/cp.2018.1257

N. Duangrit, B. Hong, A. D. Burnett, P. Akkaraekthalin, I. D. Robertson and N. Somjit, “Terahertz Dielectric Property Characterization of Photopolymers for Additive Manufacturing,” in IEEE Access, vol. 7, pp. 12339-12347, 2019. doi: 10.1109/ACCESS.2019.2893196

V. Doychinov, C. Russell, N. Somjit, I. D. Robertson, S. Chakrabarty and D. P. Steenson, “Investigation of implantable antennas for exploratory neuroscience studies,” The Loughborough Antennas & Propagation Conference (LAPC 2018), Loughborough, 2018, pp. 1-6. doi: 10.1049/cp.2018.1445

G.H. Mills, A.E. Jackson and R.C. Richardson, “Advances in the Inspection of Unpiggable Pipelines”, Robotics, 2017, 6, 36.

G.H. Mills, J.H.W. Liu JHW, B.Y. Kaddouh, A.E. Jackson and R.C. Richardson, “Miniature Magnetic Robots For In-Pipe Locomotion”, Robotics Transforming the Future – Proceedings of CLAWAR 2018: The 21st International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, pp. 289-300.

G. Jung et al., “Single-Chip Reduced-Wire CMUT-on-CMOS System for Intracardiac Echocardiography,” 2018 IEEE International Ultrasonics Symposium (IUS), Kobe, 2018, pp. 1-4. doi: 10.1109/ULTSYM.2018.8579915

Salazar Sutil N. Section Editorial: Human Movement as Critical Creativity: Basic Questions for Movement Computing. Computational Culture: a Journal of Software Studies, 2018. (6) ISSN 2047-2390