RRS: Rapidly-Exploring Random Snakes a New Method for Mobile Robot Path Planning

Baizid, Khelifa; Chellali, Ryad; Luza, R.; Vitezslav, B.; Arrichiello, Filippo

doi:10.1007/978-3-319-08338-4_22

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…According to [5] the UAV are classified into three different categories, fixed wing, flapping wing and rotary wing, within this last category are the quadrotors, which are suitable for the application of algorithms that generate trajectories, due to their characteristics of easy control, low energy consumption, high flight safety and high maneuverability. For a quadrotor to perform missions autonomously requires algorithms for the planning of safe trajectories, this is a problem that has received considerable attention in recent years, proof of this are the recent studies on trajectories for UAV as they are those of [2], [3], [7], [8] among many others, such algorithms are efficient if they can obtain a solution, if any, to complex and disordered environments [1].…”

Section: Introductionmentioning

confidence: 99%

Improvements of a three-dimensional trajectory planning algorithm for UAV navigation based on potential fields

Alberto¹,

Ardila²,

Pinzon³

2017

ces

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Path planning is a subject of wide interest in applications for unmanned aerial vehicles. A great variety of solutions have been generated to find paths free of collisions in three-dimensional scenarios, among them, the algorithm based on independent mobile points MBPF which uses the concept of artificial potential fields for the evasion of obstacles, is an algorithm that can be used in both 2D and 3D environments with static or dynamic obstacles and manages to avoid falling into local minimums. MBPF can find trajectories in a variety of complex 3D scenarios. However, it can be improved so that the trajectory reduces its distance, smooth the route and in some cases, converge. To improve the response of the algorithm, 3 improvements are proposed, one based on a modification to the original algorithm and another two based on a post processing of the result. the first improvement directly modifies the initial distribution of the starting points of the algorithm by densifying the points in the areas close to the obstacles, the two remaining improvements are made by post-processing the trajectory obtained for which Visibility Graphs are used and Active Contours. As a result, a considerable reduction 1572 Leonardo Ramírez Alberto et al. in the distance to be traveled is evidenced in the final trajectory and a greater smoothness is perceived in the curves.

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