A Mission Management Framework for Unmanned Autonomous Vehicles

Abstract

Abstract. Unmanned Autonomous Vehicles (UAVs) are increasingly deployed for missions that are deemed dangerous or impractical to perform by humans in many military and disaster scenarios. UAVs in a team need to operate in sub-groups or independently to perform specific tasks, but still synchronise state information regularly and cope with intermittent communication failures as well as permanent UAV failures. This paper describes a failure management scheme that copes with failures, which may result in disjoint sub-networks within the team. A communication management protocol is proposed to control UAVs performing disconnected individual operations, while maintaining the team's structure by trying to ensure that all members of the mission rendezvous to communicate at intermittent intervals. The evaluation of the proposed approaches shows that the schemes are scalable and perform significantly better than similar centralised approaches.

Self-Management Framework for Mobile Autonomous Systems

“…The system assumes a single certification authority (C 3 ), which issues certified public/private keys to all UAVs in the mission and maintains a Certificate Revocation List (CRL). The C-PKI system is also used to exchange a common secret key generated using the Diffie-Hellman protocol [12] between each member of the team and the commander (more details on the Security protocol can be found in [14]). …”

“…The assigned UAVs recursively repeat this process if their mission includes managing other UAVs, as a result creating a tree with the commander UAV as the root. This tree is used to communi-cate management messages, collect state information and organise the roles hierarchically each with a unique identity so as to make the team robust and capable of recovering from failure (details of tree formation and maintenance are given in [14]). …”

“…The team layer of the management framework deals with the formation of a distributed self managing team of UAVs by discovering new UAVs within the communication range of those which are already part of the team, authenticating them [14], assigning them to suitable roles based on their capabilities, and maintaining the team. The team formation process is facilitated by five interacting services residing in the team layer.…”

“…It is thus necessary to perform optimisation on the set of discovered UAVs and the mission roles in order to best utilise the available resources as first-come-first-served is suboptimal. This paper extends the architecture presented in [4,13,14] by elaborating the different components of the framework and presenting an optimisation scheme that optimally assigns available UAVs to roles based on their capabilities. The scheme considers both local assignments by the commander and global future assignments by other team members, so that the team will reach its optimal configuration provided UAVs with the necessary capabilities are available.…”

Self-management of hybrid optical and packet switching networks

“…In another work, self-management is investigated to be used in situations where there is a great risk for human beings, such as in military or disaster scenarios. Within this line of research, we point out the work by Eskindir et al [7] who has been investigating the use of self-management on Unmanned Autonomous Vehicles (UAVs). UAVs are mobile robots employed for reconnaissance in dangerous areas for human beings.…”