Autonomous systems are playing increasingly important roles in today's world. Technological advancements have allowed autonomous applications in many areas such as ground robotics (including factory robots), unmanned aerial vehicles (UAVs), unmanned underwater vehicles, unmanned spacecrafts etc. UAVs are relatively a new inclusion into the broader field of autonomous systems. The possibility of using UAVs for a diverse range of beneficial applications such as fire fighting, search and rescue missions, combating crime, etc. is a major motivational factor in this research program. Thus mission related work presented in this thesis, although generic In nature, relates heavily to UAVs. Mission planning involves many dimensions In general and the fundamental aspects explored in this research program i.e. route planning, resource allocation optimization, vehicle selection and mission collaboration, in particular. At the end of this research program a novel graph theoretic routing algorithm that offers deconfliction and efficient route computation has been developed and its performance experimentally examined using computer simulations. In addition, novel exhaustive as well as sub-optimal resource allocation mission planning schemes have been developed and applied to both deterministic and stochastic input variables. Furthermore the significant benefits obtained during a mission due to collaboration between acting UAVs have been examined and experimentally demonstrated. This collaborative behaviour has been achieved via the inclusion of data communication between UAVs and the mission Control Centre and in a way that allows for UAVs to coordinate their time of arrival to destination and thus maximize mission success.
|Source Sets||Ethos UK|
|Type||Electronic Thesis or Dissertation|
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