Research Information System
IEEE - 2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA), Sana´A, Yemen, 6 - 07 August 2024, pp.1-10, (Full Text)
Efficient path planning is critical for the safe and effective
navigation of Autonomous Aerial Robots (AARs) in complex 3D
environments. This paper presents a comprehensive exploration of path
planning techniques designed for AAR operations, with a focus on the
application of the D* algorithm and its variants. Beginning with an
overview of traditional methods such as Dijkstra's and A* algorithms,
this work delves into the advanced capabilities of the D* algorithm
family, including dynamic replanning and adaptive optimization for
changing environmental conditions. A key contribution of this work is
the implementation of these algorithms in a manner that significantly
accelerates the search phase, particularly when dealing with multiple
robots and goals, enhancing computational efficiency. Through detailed
analysis and simulation, this study investigates the practical
implementation of these algorithms in 3D space, addressing challenges
such as obstacle avoidance, computational efficiency, dynamic
feasibility, and real-time adaptability. Our simulated case results
demonstrate the efficacy and versatility of these techniques in various
AAR missions, providing valuable insights for researchers and
practitioners in the field of autonomous aerial navigation. This work
not only highlights the strengths and limitations of existing methods
but also offers novel solutions to improve the performance of path
planning algorithms in dynamic environments.