Robotic Obstacle Avoidance in a Partially Observable Environment Using Feature Ranking

Gharbieh, Waseem; Al-Mousa, Amjed

doi:10.2316/j.2019.206-5213

Cited by 1 publication

(2 citation statements)

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“…Such research typically tries to leverage collision avoidance techniques developed in the 2D domain for ground robotics and expand on them to deal with UAVs' motion in the 3D space. 14 Sampling-based algorithms are one approach that is used in path planning. 15,16 Sampling-based algorithms focus on creating new intermediate paths for moving autonomous crafts safely to their target destinations.…”

Section: Introductionmentioning

confidence: 99%

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Sampling-based unmanned aerial vehicle air traffic integration, path planning, and collision avoidance

Sababha

Al-Mousa

Baniyounisse

et al. 2022

International Journal of Advanced Robotic Systems

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Unmanned aircraft or drones as they are sometimes called are continuing to become part of more real-life applications. The integration of unmanned aerial vehicles in public airspace is becoming an important issue that should be addressed. As the number of unmanned aerial vehicles and their applications are largely increasing, air traffic with more unmanned aircraft has to be given more attention to prevent collisions and maintain safe skies. Unmanned aerial vehicle air traffic integration and regulation has become a priority to different regulatory agencies and has become of greater interest for many researchers all around the world. In this research, a sampling-based air traffic integration, path planning, and collision avoidance approach is presented. The proposed algorithm expands an existing 2D sampling-based approach. The original 2D approach deals with only two unmanned aircraft. Each of the two aircraft shares location information with a ground-based path planner computer, which would send back the avoidance waypoints after performing the 2D sampling. The algorithm proposed in this article can handle any number of drones in the 3D space by performing either 2D or 3D sampling. The proposed work shows a 10-fold enhancement in terms of the number of unmanned aerial vehicle collisions. The presented results also contribute to enabling a better understanding of what is expected of integrating more drones in dense skies.

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Section: Introductionmentioning

confidence: 99%

“…Such research typically tries to leverage collision avoidance techniques developed in the 2D domain for ground robotics and expand on them to deal with UAVs’ motion in the 3D space. 14…”

Section: Introductionmentioning

confidence: 99%