Multi-objective route planning for UAV
X Chen, R Xu, J Zhao - 2017 4th international conference on …, 2017 - ieeexplore.ieee.org
X Chen, R Xu, J Zhao
2017 4th international conference on information science and …, 2017•ieeexplore.ieee.orgThis study aimed at solving the multi-UAV route planning problem. It is necessary to
decompose the mission into sub-goals and to decide which UAV should execute which
subgoal (ie task). In an application domain, there are sixty-eight fixed locations, which are to
be inspected by four UAVs after traveling through the minimum time. An ant colony algorithm
(ACO) is used for path planning, and greedy algorithm is used for task allocation.
decompose the mission into sub-goals and to decide which UAV should execute which
subgoal (ie task). In an application domain, there are sixty-eight fixed locations, which are to
be inspected by four UAVs after traveling through the minimum time. An ant colony algorithm
(ACO) is used for path planning, and greedy algorithm is used for task allocation.
This study aimed at solving the multi-UAV route planning problem. It is necessary to decompose the mission into sub-goals and to decide which UAV should execute which subgoal (i.e. task). In an application domain, there are sixty-eight fixed locations, which are to be inspected by four UAVs after traveling through the minimum time. An ant colony algorithm (ACO) is used for path planning, and greedy algorithm is used for task allocation.
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