A Range-Based Algorithm for Autonomous Navigation of an Aerial Drone to Approach and Follow a Herd of Cattle
| Autor: | Jay Katupitiya, Andrey V. Savkin, Manaram Gnanasekera, A.H.T. Eranga De Silva |
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| Rok vydání: | 2021 |
| Předmět: |
herding
Computer science aerial drones TP1-1185 UAVs Biochemistry Sliding mode control Article Analytical Chemistry Robustness (computer science) Range (statistics) Animals Electrical and Electronic Engineering range-based guidance Instrumentation Chemical technology sliding mode control animal farming range only measurements Atomic and Molecular Physics and Optics Drone Herd Cattle Noise (video) unmanned aerial vehicles Noise autonomous navigation Algorithm Algorithms |
| Zdroj: | Sensors (Basel, Switzerland) Sensors Volume 21 Issue 21 Sensors, Vol 21, Iss 7218, p 7218 (2021) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s21217218 |
| Popis: | This paper proposes an algorithm that will allow an autonomous aerial drone to approach and follow a steady or moving herd of cattle using only range measurements. The algorithm is also insensitive to the complexity of the herd’s movement and the measurement noise. Once arrived at the herd of cattle, the aerial drone can follow it to a desired destination. The primary motivation for the development of this algorithm is to use simple, inexpensive and robust sensing hence range sensors. The algorithm does not depend on the accuracy of the range measurements, rather the rate of change of range measurements. The proposed method is based on sliding mode control which provides robustness. A mathematical analysis, simulations and experimental results with a real aerial drone are presented to demonstrate the effectiveness of the proposed method. |
| Databáze: | OpenAIRE |
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