Cooperative path planning with applications to target tracking and obstacle avoidance for multi-UAVs

This paper proposes a novel Dynamic Adaptive Ant Lion Optimizer (DAALO) for route planning of unmanned aerial vehicle. Ant Lion Optimizer (ALO) is a new intelligent algorithm motivated by the phenomenon that antlions hunt ants in nature, showing the great potential to solve the optimization problems of engineering. In the proposed DAALO, the random walk of ants is replaced by Levy flight to make ALO escape from local optima more easily. Besides, by introducing the improvement rate of population as the feedback, the size of trap is adjusted dynamically based on the 1/5 Principle to improve the performance of ALO including convergence accuracy, convergence speed and stability. Compared to some other bio-inspired methods, the proposed algorithm are utilized to find the optimal route in two different environments such as mountain model and city model. The comparison results demonstrate the effectiveness, robustness and feasibility of DAALO.

Dynamic Adaptive Ant Lion Optimizer applied to route planning for unmanned aerial vehicle

UAV feasible path planning based on disturbed fluid and trajectory propagation

Path planning is the essential aspect of autonomous flight system for unmanned aerial vehicles (UAVs). An improved particle swarm optimization (PSO) algorithm, named GBPSO, is proposed to enhance t...

UAV Path Planning Based on Particle Swarm Optimization with Global Best Path Competition

has surged in the last two decades, making them popular in- struments for a wide range of applications, and leading to a remarkable number of scientific contributions in geoscience, remote sensing and engineering. However, the development of best practices for high quality of UAV mapping are often overlooked representing a drawback for their wider adoption. UAV solutions then require an inter-disciplinary research, integrating different expertise and combining several hardware and software com- ponents on the same platform. Despite the high number of peer-reviewed papers on UAVs, little attention has been given to the interaction between research topics from different domains (such as robotics and computer vision) that impact the use of UAV in remote sensing. The aim of this paper is to (i) review best practices for the use of UAVs for remote sensing and mapping applications and (ii) report on current trends - including adjacent domains - for UAV use and discuss their future impact in photogrammetry and remote sensing. Hardware developments, navigation and acquisition strategies, and emerging solutions for data processing in innovative applications are considered in this analysis. As the number and the heterogeneity of debated topics are large, the paper is organized according to very specific questions considered most relevant by the authors.

UAV in the advent of the twenties: Where we stand and what is next

Three-dimensional Path Planning for Unmanned Aerial Vehicle Based on Interfered Fluid Dynamical System

In view of the existing methods to calculate collision region using certain threshold value of distance or time,an unmanned aerial vehicle( UAV) dynamic collision region model based on maneuver information of both UAV and aerial intruder was presented. Firstly,the no-maneuver collision region was proposed. In this region,UAV and intruder would undergo collision if UAV didn't execute any avoidance maneuver. Using a geometric method,a mathematical model of no-maneuver collision region was formulated utilizing the motion states of UAV and intruder,and minimum safety distance,etc. Secondly,the constraints on the UAV maneuverability were added to calculate the maximum maneuverability collision region,which was the border for UAV to avoid the collision by maximum maneuverability flight. Thirdly,the concept of non-escape region was proposed. Then the safe flight envelope was presented. This safe flight envelope was a boundary line of avoiding a collision with aerial intruder for UAV. Finally,the key factors of the proposed regions were analyzed by theoretical derivation combined with simulation. The results show that the presented collision regions are useful for UAV to select and evaluate the avoidance maneuver,and to decide whether to execute maximum maneuverability flight. The presented collision regions provide a practical guideline for UAV to ensure safe collision avoidance.

Yao Peng

Papers

Three-dimensional Path Planning for Unmanned Aerial Vehicle Based on Interfered Fluid Dynamical System

Modeling and analysis of dynamic collision region for UAV avoiding aerial intruders