A multi-scroll chaotic system for a higher coverage path planning of a mobile robot using flatness controller

Nasr, Salah; Mekki, Hassen; Bouallegue, Kaïs

doi:10.1016/j.chaos.2018.12.002

Cited by 73 publications

(23 citation statements)

References 28 publications

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“…The authors of [21] have explained that most of the existing algorithms employ the same sweep direction in all subareas which may not be able to obtain optimal results. Recently, various approaches have been proposed to compute a low cost coverage path such as mirror mapping method [22], viewpoints sampling [23], in-field obstacles classification [24], optimal polygon decomposition [25], and context-aware UAV mobility [26]. Despite the success of such techniques, in most cases, either many locations of the target area are covered repeatedly, or computing time degrades [27].…”

Section: Introductionmentioning

confidence: 99%

A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

Majeed

Lee

2019

Applied Sciences

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This paper presents a new coverage flight path planning algorithm that finds collision-free, minimum length and flyable paths for unmanned aerial vehicle (UAV) navigation in three-dimensional (3D) urban environments with fixed obstacles for coverage missions. The proposed algorithm significantly reduces computational time, number of turns, and path overlapping while finding a path that passes over all reachable points of an area or volume of interest by using sensor footprints’ sweeps fitting and a sparse waypoint graph in the pathfinding process. We devise a novel footprints’ sweep fitting method considering UAV sensor footprint as coverage unit in the free spaces to achieve maximal coverage with fewer and longer footprints’ sweeps. After footprints’ sweeps fitting, the proposed algorithm determines the visiting sequence of footprints’ sweeps by formulating it as travelling salesman problem (TSP), and ant colony optimization (ACO) algorithm is employed to solve the TSP. Furthermore, we generate a sparse waypoint graph by connecting footprints’ sweeps’ endpoints to obtain a complete coverage flight path. The simulation results obtained from various scenarios fortify the effectiveness of the proposed algorithm and verify the aforementioned claims.

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Section: Introductionmentioning

confidence: 99%

A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

Majeed

Lee

2019

Applied Sciences

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“…In order to design a seemingly random motion that will also guarantee efficient grid exploration, many researchers have considered chaotic path planning [2,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. In this approach, a chaotic dynamical system is utilized to generate a chaotic motion trajectory, that is then performed by the robot to achieve efficient coverage.…”

Section: Introductionmentioning

confidence: 99%

An Inverse Pheromone Approach in a Chaotic Mobile Robot’s Path Planning Based on a Modified Logistic Map

et al. 2019

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One major topic in the research of path planning of autonomous mobile robots is the fast and efficient coverage of a given terrain. For this purpose, an efficient method for covering a given workspace is proposed, based on chaotic path planning. The method is based on a chaotic pseudo random bit generator that is generated using a modified logistic map, which is used to generate a chaotic motion pattern. This is then combined with an inverse pheromone approach in order to reduce the number of revisits in each cell. The simulated robot under study has the capability to move in four or eight directions. From extensive simulations performed in Matlab, it is derived that motion in eight directions gives superior results. Especially, with the inclusion of pheromone, the coverage percentage can significantly be increased, leading to better performance.

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“…At the boundary conditions, in order not to leave the workspace, a mirror mapping method is utilized, which constrains all the mobile robot positions in the workspace and which can reflect all the overflow waypoints returning to it. Compared with simply using the double-scroll chaotic systems in the whole workspace, the suggested new multi-scroll chaotic system, combined with the mirror mapping method, shows good results that can achieve a higher coverage for a larger workplace of the mobile robot (Nasr et al 2019). The above path planning strategies can fulfill the requirements of covering the entire search area, but still need to be improved for search efficiency.…”

Section: Introductionmentioning

confidence: 99%

Efficient Path Planning Method of USV for Intelligent Target Search

Zhang

Liu

et al. 2019

J geovis spat anal

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In order to accomplish a target search task safely and efficiently and make full use of prior information and real-time information, a path planning method of unmanned surface vehicle (USV) for intelligent target search is proposed. The overall strategy is divided into three parts: global path planning based on prior information, local path planning based on real-time information, and improved A* obstacle avoidance algorithm. Before the start of the task, the global path planning is carried out based on prior information such as the initial position of USV, the predicted position of the target and range of search area. After the start of the task, if USV finds suspicious targets, in order to further approach these suspicious targets, it will enter different local path planning modes according to the characteristics of these targets. During task execution, if obstacles are encountered, an improved A* obstacle avoidance algorithm is adopted. The simulation results show that the proposed method can improve the efficiency of target recognition and reduce the turning cost of USV when encountering obstacles. So, for USV intelligent target search, the proposed path planning method can save resources and improve search efficiency.

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A multi-scroll chaotic system for a higher coverage path planning of a mobile robot using flatness controller

Cited by 73 publications

References 28 publications

A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

An Inverse Pheromone Approach in a Chaotic Mobile Robot’s Path Planning Based on a Modified Logistic Map

Efficient Path Planning Method of USV for Intelligent Target Search

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