scholarly journals Path Planning and Obstacle Avoidance for UAV in an Uncharted Environment

2021 ◽  
Vol 9 (8) ◽  
pp. 2353-2359
Author(s):  
Shubhankar Goje
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Obstacle Avoidance ◽  
Obstacle Detection ◽  
Ongoing Research ◽  
Robot Operating System ◽  
Aerial Vehicles ◽  
Different Types ◽  
Infinite Loop

Abstract: The growing industry of unmanned aerial vehicles (UAV) requires an efficient and robust algorithm to decide the path of the UAV and avoid obstacles. The study of pathfinding algorithms is ongoing research not just useful in the domain of drones, but in other fields like video games (AI pathfinding), terrain traversal (mapped, unmapped, areal, underwater, land, etc.), and industries that require robots to deliver packages. This paper proposes a new pathfinding algorithm that aims to solve the problem of pathfinding in unknown 2-dimensional terrain. Based on a system of assumptions and using the help of a set of sensors aboard the UAV, the algorithm navigates the UAV from a start point to an endpoint while avoiding any shape or size of obstacles in between. To avoid multiple different types of “infinite loop” situations where the UAV gets stuck around an obstacle, a priority-based selector for intermediate destinations is created. The algorithm is found to work effectively when simulated in Gazebo on Robot Operating System (ROS). Keywords: Path Planning, UAV, Obstacle Avoidance, Drone Navigation, Obstacle Detection, Uncharted Environment.

scholarly journals A Robot Operating System Framework for Secure UAV Communications

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1369
Author(s):  
Hyojun Lee ◽  
Jiyoung Yoon ◽  
Min-Seong Jang ◽  
Kyung-Joon Park
Keyword(s):  
Operating System ◽  
Unmanned Aerial Vehicles ◽  
Ground Control ◽  
Unmanned Aerial System ◽  
Security Framework ◽  
Security Vulnerabilities ◽  
Robot Operating System ◽  
Security Issues ◽  
Aerial Vehicles ◽  
Ground Control Station

To perform advanced operations with unmanned aerial vehicles (UAVs), it is crucial that components other than the existing ones such as flight controller, network devices, and ground control station (GCS) are also used. The inevitable addition of hardware and software to accomplish UAV operations may lead to security vulnerabilities through various vectors. Hence, we propose a security framework in this study to improve the security of an unmanned aerial system (UAS). The proposed framework operates in the robot operating system (ROS) and is designed to focus on several perspectives, such as overhead arising from additional security elements and security issues essential for flight missions. The UAS is operated in a nonnative and native ROS environment. The performance of the proposed framework in both environments is verified through experiments.

scholarly journals Modelling and Simulation of Distributed UAV Swarm Cooperative Planning and Perception

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haifeng Ling ◽  
Hongchuan Luo ◽  
Haisong Chen ◽  
Linyuan Bai ◽  
Tao Zhu ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Real World ◽  
Simulation Platform ◽  
Real World Application ◽  
Aerial Vehicles ◽  
Uav Swarm ◽  
Different Types ◽  
Simulation Results ◽  
Cooperative Planning

As an emerging topic, the swarm of autonomous unmanned aerial vehicles (UAVs) has been attracting great attention. Due to the indeterminacy of sensors, distributed cooperative swarms have been considered to be efficient and robust but challenging to design and test. To facilitate the development of distributed swarms, it has been proposed to utilise a simulation platform for cooperative UAVs using imperfect perception. However, the existing simulation platforms cannot satisfy this demand due to a few reasons. First, they are designed for a specific purpose, and their functionalities are difficult to extend. Second, the existing platforms lack compatibility to be applied to different types of scenarios. Third, the modelling of these platforms is too simplified to simulate flight motion dynamic and noisy communication accurately, which may cause a difference in performance between the simulation and real-world application. To address the mentioned issues, this paper models the problem and proposes a simulation platform for distributed swarm cooperative perception, which addresses software engineering concerns and provides a set of extendable functionalities of a cooperative swarm, including communication, estimation, perception fusion, and path planning. The applicability of the proposed platform is verified by simulations with the real-world application. The simulation results demonstrate that the proposed system is viable.

Cooperative Path Planning of Unmanned Aerial Vehicles

2010 ◽  
Author(s):  
Antonios Tsourdos ◽  
Brian White ◽  
Madhavan Shanmugavel
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles

Optimal path planning with modified A-Star algorithm for stealth unmanned aerial vehicles in 3D network radar environment

2021 ◽  
pp. 095441002110073
Author(s):  
Zhe Zhang ◽  
Jian Wu ◽  
Jiyang Dai ◽  
Cheng He
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Optimal Path ◽  
Radar System ◽  
Planning Method ◽  
Optimal Path Planning ◽  
Aerial Vehicles ◽  
3D Network ◽  
Planning Scheme ◽  
Estimation Function

For stealth unmanned aerial vehicles (UAVs), path security and search efficiency of penetration paths are the two most important factors in performing missions. This article investigates an optimal penetration path planning method that simultaneously considers the principles of kinematics, the dynamic radar cross-section of stealth UAVs, and the network radar system. By introducing the radar threat estimation function and a 3D bidirectional sector multilayer variable step search strategy into the conventional A-Star algorithm, a modified A-Star algorithm was proposed which aims to satisfy waypoint accuracy and the algorithm searching efficiency. Next, using the proposed penetration path planning method, new waypoints were selected simultaneously which satisfy the attitude angle constraints and rank-K fusion criterion of the radar system. Furthermore, for comparative analysis of different algorithms, the conventional A-Star algorithm, bidirectional multilayer A-Star algorithm, and modified A-Star algorithm were utilized to settle the penetration path problem that UAVs experience under various threat scenarios. Finally, the simulation results indicate that the paths obtained by employing the modified algorithm have optimal path costs and higher safety in a 3D complex network radar environment, which show the effectiveness of the proposed path planning scheme.

Optimizing Perimeter Surveillance Drones to enhance the security system of unmanned aerial vehicles

2021 ◽  
Vol 2 (2) ◽  
pp. 105-115
Author(s):  
Mahmod Al-Bkree
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Security System ◽  
Small Scale ◽  
Security Systems ◽  
Ongoing Research ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Initial Results

This work is to optimize perimeter surveillance and explore the distribution of ground bases for unmanned aerial vehicles along the Jordanian border and optimize the set of technologies for each aerial vehicle. This model is part of ongoing research on perimeter security systems based on unmanned aerial vehicles. The suggested models give an initial insight about selecting technologies carried by unmanned aerial vehicles based on their priority; it runs for a small scale system that can be expanded, the initial results show the need for at least four ground bases along the length of the border, and a selected set of various technologies for each vehicle.

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