Filtered Medial Surface Based Approach for 3D Collision-Free Path Planning Problem

Karima Benzaid,Ouiddad Labbani-Igbida,Noura Mansouri,Romain Marie

doi:10.1155/2018/4676720

Karima Benzaid, Ouiddad Labbani-Igbida + Show 2 more

Open Access

https://doi.org/10.1155/2018/4676720

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Abstract

This paper introduces an original 3D path planning approach for Unmanned Aerial Vehicle (UAV) applications. More specifically, the core idea is to generate a smooth and collision-free path with respect to the vehicle dimension. Given a 3D grid representation of the environment, the Generalized Voronoi Graph (GVG) is first approximated using a filtered medial surface (FMS) algorithm on the corresponding navigable space. Based on an efficient pruning criterion, the produced FMS excludes GVG portions corresponding to narrow passages unfitting safe UAV navigation constraints, and thus it defines a set of guaranteed safe trajectories within the environment. Given a set of starting and destination coordinates, an adapted A-star algorithm is then applied to compute the shortest path on the FMS. Finally, an optimization process ensures the smoothness of the final path by fitting a set of 3D Bézier curves to the initial path. For a comparative study, the A-star algorithm is applied directly on the input environment representation and relevant comparative criteria are defined to assert the proposed approach using simulation results.

Highlights

This paper deals with the issue of 3D path planning for Unmanned Aerial Vehicle (UAV) in a known environment with stationary obstacles
In order to illustrate how the filtered medial surface (FMS) extracted by skeletonization depends on the UAV size, we have considered the same environment representation for two different UAV sizes
We present an efficient solution for 3D path planning problem in aerial robotics

Summary

Introduction

This paper deals with the issue of 3D path planning for UAVs in a known environment with stationary obstacles. Among the most known sampling based algorithms, we can cite the Rapidly Exploring Random Tree (RRT) [10] and the Probabilistic Road-Maps (PRM) [11] algorithms These methods are initially designed for 2D path planning problems based on the sampling of the configuration space. The drawback of this kind of algorithms is that they return nonoptimal solutions [12]. We propose a novel approach based on the skeletonization of the navigable space along with an adapted A-star path planner for aerial vehicles. Since the returned path is not smooth due to the continuous heading changes of the A-star path, a smoothing method is applied This may appear similar to the idea adopted in [29].

Path Planning on the Environments GVG

Smoothing the Planned Path

Results and Discussions

Conclusion and Future Works