Fast and efficient visible trajectories planning for the Dubins UAV model in 3D built-up environments

Robotica ◽  
2013 ◽  
Vol 32 (1) ◽  
pp. 143-163 ◽  
Author(s):  
Oren Gal ◽  
Yerach Doytsher
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Urban Environment ◽  
Trajectory Planning ◽  
Analytic Solution ◽  
Urban Environments ◽  
Planning Method ◽  
Time Step ◽  
Environment Model ◽  
Aerial Vehicles ◽  
Velocity Obstacle

SUMMARYIn this paper, we study the visible trajectories planning for unmanned aerial vehicles (UAVs) modeled with a Dubins airplane in 3D urban environments. Our method is based on a fast and exact spatial visibility analysis of the 3D visibility problem from a viewpoint in 3D built-up environments. We consider the 3D urban environment buildings modeled as cubes (3D boxes) and present an analytic solution to the visibility problem. Based on an analytic solution, the algorithm computes the exact visible and hidden parts from a viewpoint in the urban environment. We present a local trajectory planner generating the most visible trajectory in a known 3D urban environment model, taking into account the dynamic and kinematic UAV constraints. The planner computes, at each time step, the next UAV's attainable velocities and explores the most visible node, while avoiding buildings as static obstacles in the environments, using the velocity obstacle method. The visibility type of the trajectory can be configured beforehand as visible roofs and surfaces in the environments. We demonstrate our visibility and trajectory planning method in simulations in several 3D urban environments, showing visible trajectory planning capabilities.

scholarly journals Communication-Aware Trajectory Planning for Unmanned Aerial Vehicles in Urban Environments

2018 ◽  
Vol 41 (10) ◽  
pp. 2271-2282 ◽  
Author(s):  
Hyondong Oh ◽  
Hyo-Sang Shin ◽  
Seungkeun Kim ◽  
Wen-Hua Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Trajectory Planning ◽  
Urban Environments ◽  
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.

scholarly journals Distributed Cooperative Avoidance Control for Multi-Unmanned Aerial Vehicles

Actuators ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Sunan Huang ◽  
Rodney Swee Huat Teo ◽  
Wenqi Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Case Studies ◽  
Collision Avoidance ◽  
Hardware In The Loop ◽  
Crucial Issue ◽  
Communication Failure ◽  
Aerial Vehicles ◽  
Avoidance Control ◽  
Velocity Obstacle ◽  
Multi Uav

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method.

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

scholarly journals Collective Perception Using UAVs: Autonomous Aerial Reconnaissance in a Complex Urban Environment

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2926
Author(s):  
Petr Stodola ◽  
Jan Drozd ◽  
Karel Šilinger ◽  
Jan Hodický ◽  
Dalibor Procházka
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Urban Environment ◽  
Computer Simulations ◽  
Optimal Solutions ◽  
Uneven Terrain ◽  
Area Of Interest ◽  
Aerial Vehicles ◽  
Benchmark Instances ◽  
Aerial Reconnaissance

This article examines autonomous reconnaissance in a complex urban environment using unmanned aerial vehicles (UAVs). Environments with many buildings and other types of obstacles and/or an uneven terrain are harder to be explored as occlusion of objects of interest may often occur. First, in this article, the problem of autonomous reconnaissance in a complex urban environment via a swarm of UAVs is formulated. Then, the algorithm based on the metaheuristic approach is proposed for a solution. This solution lies in deploying a number of waypoints in the area of interest to be explored, from which the monitoring is performed, and planning the routes for available UAVs among these waypoints so that the monitored area is as large as possible and the operation as short as possible. In the last part of this article, two types of main experiments based on computer simulations are designed to verify the proposed algorithms. The first type focuses on comparing the results achieved on the benchmark instances with the optimal solutions. The second one presents and discusses the results obtained from a number of scenarios, which are based on typical reconnaissance operations in real environments.

Sign in / Sign up

Export Citation Format

Share Document