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
Robotica ◽  
2013 ◽  
Vol 32 (1) ◽  
pp. 143-163 ◽  
Author(s):  
Oren Gal ◽  
Yerach Doytsher

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.


Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao

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.


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