A COMPREHENSIVE STUDY OF PATH PLANNING TECHNIQUES FOR MULTIROTOR AERIAL VEHICLES (MAVs) BASED ON MODEL PREDICTIVE CONTROL

Abstract

Multirotor unmanned aerial vehicles (MAVs) are increasingly used in civil and military applications as potential solutions for many applications. A primary feature of MAVs is the ability to perform automatic real-time path planning to generate feasible and optimal paths to a predetermined target point, satisfy the constraints of the control system and/or the environment. In particular, predictive control models have emerged as an optimal method to solve the path planning problem for MAVs. This paper uses the synthesis, analysis, and comparison methods to provide an overview of the path planning problem for MAVs from studies in the past ten years. Accordingly, in addition to classifying and listing specific methods, we also fully survey studies applying predictive control models, thereby recognize the contributions and limitations of each approach to make useful assessments. The results of the paper can help scientists identify the challenges and future directions for this field to choose appropriate research directions.