Path Planning for Autonomous Drones: Challenges and Future Directions

Abstract

Unmanned aerial vehicles (UAV), or drones, have gained a lot of popularity over the last decade. The use of autonomous drones appears to be a viable and low-cost solution to problems in many applications. Path planning capabilities are essential for autonomous control systems. An autonomous drone must be able to rapidly compute feasible and energy-efficient paths to avoid collisions. In this study, we review two key aspects of path planning: environmental representation and path generation techniques. Common path planning techniques are analyzed, and their key limitations are highlighted. Finally, we review thirty-five highly cited publications to identify current trends in drone path planning research. We then use these results to identify factors that need to be addressed in future studies in order to develop a practical path planner for autonomous drones.

Suboptimal Trajectory Planning Technique in Real UAV Scenarios with Partial Knowledge of the Environment

“…Then, Equation ( 13) must be rearranged in a matrix structure to be inserted in the QP, Equation (8). By introducing n c additional intermediate points and projecting vector d i (t) on the three-world axis x W , y W , and z W , Equation ( 13) becomes…”

“…Path planners can be classified into two main categories in relation to the way the computations are carried out. In particular, they can be divided into offline and online algorithms [8]. The offline algorithms plan the trajectory before the takeoff; hence, they need information about the environment (such as obstacles and fly-zones) in advance [9,10].…”

Design and Development of an Air–Land Amphibious Inspection Drone for Fusion Reactor

“…Currently, many factors are hindering the application of miniature mobile platforms for drones, such as unstructured environments (stairs, rubble, undulating terrain, etc.) [21][22][23]. Secondly, the miniaturization of the power supply also makes it difficult to keep up with other key devices (e.g., actuators, sensors, and calculators), which creates difficulties in the design of mobile platforms [24,25].…”

Comprehensive Investigation of Unmanned Aerial Vehicles (UAVs): An In-Depth Analysis of Avionics Systems

“…Concerning the You Only Look Once (YOLO) algorithm used for real-time detection and classification of multiple targets, the work in [59] investigated the integration of YOLO with UAV technology and the corresponding practical applications (e.g., engineering, transportation, automation, etc.). Given that path planning holds significance in the context of drone autonomy, the authors of [60] reviewed the environmental representation as well as the path generation techniques for drones. Considering the potential of UAVs in warehouse management, a systematic literature review was conducted in [61], enriching the background of knowledge about the obstacles versus the adoption of UAVs in warehouse handling, unlike in [62], where the review primarily focused on the role of drones in flood management.…”

“…As can be noted from the literature survey encompassing the modern reviews in [46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63], the majority of these articles actually focus on the UAV domain of usage and application fields. In other terms, there exist no reviews about the drones themselves, involving different architectures, structures, avionics, and software-to-hardware branches (i.e., the results of algorithms over the behavioral mechanism of sensors).…”