Sporadic access control and artificial Intelligence for future robotic systems

  • Sporadic access control and artificial Intelligence for future robotic systems

School of Electronics, Electrical Engineering and Computer Science
& ECIT Global Research Institute

Proposed Project Title: Sporadic access control and artificial Intelligence for future robotic systems

Principal Supervisor:   Dr Youngwook Ko                                Second Supervisor: Dr. Emi Garcia-Palacios

Project Description:

As manufacturing and robotic applications become more sophisticated, the need for autonomous systems that can operate intelligently with minimal human interventions increases. For a large-scale intelligence, a large number of machines/sensors in- and around industrial energy and robotic environments is deployed (e.g., at least 200 sensors per mobile robot). Current research has attempted to improve the latency and reliability of wireless network in today and future machine type communications (MTC) standards (e.g., see Zigbee (IEEE 802.15.4), Bluetooth (IEEE 802.15.1), 3GPP’s M2M), considering both cellular systems and non-cellular applications. However, autonomous control at the wireless connectivity of many such systems is opaque and far behind the industrial requirements. The network disruption caused in dynamic robotic environments needs special attention.

This PhD programme will investigate various features for autonomous multiple access control (a-MAC) algorithms with sporadically connected-devices. For this, the project will develop new machine learning techniques to be applied to both the Physical and upper layers of wireless robotic-sensing networks. For example, a variety of machines within an electric vehicle coexist being interferer to other and interfere by other, simultaneously. This project aims to develop opportunities for autonomously integrating the pricing of local machine resource and the cognitive cooperation principles so that a full robotics autonomy can be enabled, taking into account fidelity-flexibility trade-offs ascertained at various system environments.


Contact details

Supervisor Name: Youngwook Ko                                     Tel: +44 (0)28 9097 1772
QUB Address:                                                                 Email: y.ko@qub.ac.uk
ECIT Institute,
Queen's Road
Queen's University Belfast
Northern Ireland Science Park
Belfast,
BT3 9DT, UK