Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study
Autor: | Mohammadreza Radmanesh, Paul H. Guentert, Manish Kumar, Mohammad Sarim |
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Rok vydání: | 2018 |
Předmět: |
0209 industrial biotechnology
Control and Optimization Sense and avoid Computer science Real-time computing Aerospace Engineering 02 engineering and technology 020901 industrial engineering & automation Control and Systems Engineering Algorithmic efficiency Automotive Engineering Obstacle avoidance 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Motion planning |
Zdroj: | Unmanned Systems. :95-118 |
ISSN: | 2301-3869 2301-3850 |
DOI: | 10.1142/s2301385018400022 |
Popis: | Unmanned aerial vehicles (UAVs) have recently attracted the attention of researchers due to their numerous potential civilian applications. However, current robot navigation technologies need further development for efficient application to various scenarios. One key issue is the “Sense and Avoid” capability, currently of immense interest to researchers. Such a capability is required for safe operation of UAVs in civilian domain. For autonomous decision making and control of UAVs, several path-planning and navigation algorithms have been proposed. This is a challenging task to be carried out in a 3D environment, especially while accounting for sensor noise, uncertainties in operating conditions, and real-time applicability. Heuristic and non-heuristic or exact techniques are the two solution methodologies that categorize path-planning algorithms. The aim of this paper is to carry out a comprehensive and comparative study of existing UAV path-planning algorithms for both methods. Three different obstacle scenarios test the performance of each algorithm. We have compared the computational time and solution optimality, and tested each algorithm with variations in the availability of global and local obstacle information. |
Databáze: | OpenAIRE |
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