Indoor UAV scheduling with Restful Task Assignment Algorithm
  Research in UAV scheduling has obtained an emerging interest from scientists
in the optimization field. When the scheduling itself has established a strong
root since the 19th century, works on UAV scheduling in indoor environment has
come forth in the latest decade. Several works on scheduling UAV operations in
indoor (two and three dimensional) and outdoor environments are reported. In
this paper, a further study on UAV scheduling in three dimensional indoor
environment is investigated. Dealing with indoor environment\textemdash where
humans, UAVs, and other elements or infrastructures are likely to coexist in
the same space\textemdash draws attention towards the safety of the operations.
In relation to the battery level, a preserved battery level leads to safer
operations, promoting the UAV to have a decent remaining power level. A
methodology which consists of a heuristic approach based on Restful Task
Assignment Algorithm, incorporated with Particle Swarm Optimization Algorithm,
is proposed. The motivation is to preserve the battery level throughout the
operations, which promotes less possibility in having failed UAVs on duty. This
methodology is tested with 54 benchmark datasets stressing on 4 different
aspects: geographical distance, number of tasks, number of predecessors, and
slack time. The test results and their characteristics in regard to the
proposed methodology are discussed and presented.
