Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges

By Shubhani Aggarwal, Neeraj Kumar. Computer Communications, 2020

855 citations recorded by the source corpus.

Abstract Path planning is one of the most important problems to be explored in unmanned aerial vehicles (UAVs) for finding an optimal path between source and destination. Although, in literature, a lot of research proposals exist on the path planning problems of UAVs but still issues of target location and identification persist keeping in view of the high mobility of UAVs. To solve these issues in UAVs path planning, optimal decisions need to be taken for various mission-critical operations performed by UAVs. These decisions require a map or graph of the mission environment so that UAVs are aware of their locations with respect to the map or graph. Keeping focus on the aforementioned points, this paper analyzes various UAVs path planning techniques used over the past many years. The aim of path planning techniques is not only to find an optimal and shortest path but also to provide the collision-free environment to the UAVs. It is important to have path planning techniques to compute a safe path in the shortest possible time to the final destination. In this paper, various path planning techniques for UAVs are classified into three broad categories, i.e., representative techniques, cooperative techniques, and non-cooperative techniques. With these techniques, coverage and connectivity of the UAVs network communication are discussed and analyzed. Based on each category of UAVs path planning, a critical analysis of the existing proposals has also been done. For better understanding, various comparison tables using parameters such as-path length, optimality, completeness, cost-efficiency, time efficiency, energy-efficiency, robustness and collision avoidance are also included in the text. In addition, a number of open research problems based on UAVs path planning and UAVs network communication are explored to provide deep insights to the readers.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/eb615e3ae2610df856f338ea64473038f61d83b2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022, methodology): “One example is the work of Aggarwal and kumar [67] where path planning techniques are classiﬁed into representative techniques, cooperative techniques, and noncooperative techniques. c) Collision-avoidance systems: As UAVs ﬂy around the air, often at speed, they pose a high collision risk, whether…”
Collaborative Multi-Robot Search and Rescue: Planning, Coordination, Perception, and Active Vision (2020, background): “A detailed description of path planning algorithms including approaches of linear programming, control theory, multi-objective optimization models, probabilistic models, and meta-heuristic models for different types of UAVs is available in [133].”