Authors:
Zamoum Housseyn
1
;
Guiatni Mohamed
2
;
Bouzid Yasser
2
;
Alouane Amine
2
and
Khelal Atmane
1
Affiliations:
1
Guidance and Navigation Laboratory, Ecole Militaire Polytechnique, Algiers, Algeria
;
2
Control of Complex Systems and Simulators Laboratory, Ecole Militaire Polytechnique, Algiers, Algeria
Keyword(s):
Path Planning, Sampling-Based Methods, Random Geometric Model, UAMs, UAV Manipulator.
Abstract:
This paper presents a new approach to path planning for unmanned aerial manipulator systems (UAMs) using Sampling-Based Methods and Random Geometric Models (RGM) to efficiently search the configuration space for feasible, collision-free paths. The RGM generates random points in the UAM’s workspace to guide sampling-based algorithms in constructing graphs that link the aerial manipulator’s initial and final positions. These graphs are then explored using the RRT ∗ algorithm to find an optimal collision-free path. The effectiveness of this approach is demonstrated through different scenarios, showing that it outperforms existing path planning techniques in terms of efficiency, computing time, and robustness. The proposed framework is adaptable to various application scenarios and environments, making it a valuable tool for applications such as search and rescue missions, surveillance, and inspection tasks.