Path planning for multi-copter UAVs using tutorial training and self learning inspired teaching-learning-based optimization
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https://doi.org/10.54939/1859-1043.j.mst.87.2023.32-39Keywords:
Path planning; Teaching learning-based optimization; Optacle avoidance; UAV; Drone; Multi-copter.Abstract
Route preparation for drones is a complex method to achieve an optimal path and meet constraints following specific tasks. This paper addresses the problem of a planning method for a multi-copter unmanned aerial vehicle (UAV) to examine ground surfaces. A multi-objective route planning algorithm, named the tutorial training and self learning inspired teaching learning-based optimization (TS-TLBO), is then introduced to create a feasible and flyable path while avoiding obstacles. Here, we firstly select a joint cost function that includes different constraints to improve operational safety, at the same time, to meet task requirements. The path-tracking scheme is then applied in the quadcopter to verify the proposed approach. Experiment results show the workability of our proposed path planning process.
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