15.30-16.00 Persistent Aerial Surveillance using a Small Unmanned
Aircraft
Dr Stephen D. Prior, Reader in Unmanned
Air Vehicles, University of Southampton
This session will consider the design and
development of a range of UAV technology platforms. Attention will be paid to the
challenges of utilizing small UAVs and how
to overcome such problems, with a particular focus on alternative power sources,
such as new batteries chemistries, as well
as tethered applications.
16.00-16.30 Implications of Bio-inspired approaches in Autonomous
Mission Management Systems
Professor Samia Nefti-Meziani, Professor
of Artificial Intelligence and Robotics, University of Salford
tion captures some of our recent developments in the context of microscopic swarm
modelling of moving agent under GAMMA
Programme. Growing Autonomous Mission Management Applications (GAMMA)
is a three year £9.1 million, Autonomous
Systems programme aimed at driving SME
engagement and developing technology
within the emerging autonomous systems
markets. GAMMA technology areas of interest includes data management, image
processing, sensing and communication,
Mission planning and mission management. University of Salford is the leading
partner in Autonomous mission planning
and management, task allocation, hybrid
optimization techniques, and intelligent
decision making.
16.30 End of Technology & Regulation Conference
Exhibition open until 18.00
Mission Planning and Management systems provide tools for defining mission
objectives, distributing resources to assets
and allocating assets to mission objectives,
laying out a plan to achieve the mission
objectives using the allocated assets, overseeing operation of a mission in real-time,
detect contingencies, and mechanisms to
deal with them such as plan reconfiguration, re-planning, mission objective alteration and modification, and asset re-tasking. Navigation and path optimization are
essential components of such systems.
Bio-inspired algorithms are increasingly
becoming more popular in the context of
robotics due to their advance learning capabilities, their resilience to noise and their
implementation simplicity. This presenta20