Journal of Electronic Science and Technology, Volume. 22, Issue 4, 100277(2024)
Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones
Fig. 3. Selection of observers in (a) normal case and (b) case when one robot qualifies as both a central observer and a side observer.
Fig. 7. Cases when Straight angular velocity with unequal side obstacle detections: (a) right obstacle is closer; (b) left obstacle is closer.
Fig. 8. Cases when Straight angular velocity with equal obstacle detections and goal side of (a) Left, (b) Straight, and (c) Right.
Fig. 9. Cases when (a) central and left observers detect an obstacle as Close and right observer detects Not Detected; (b) current angular velocity is Left and the obstacles are detected as Close by both the left and right observers.
Fig. 10. Cases when the current angular velocity is Left and (a) left and right observers’ detections are same to each other; (b) right observer’s detection is closer than that of left observer; (c) left observer’s detection is closer than that of right observer.
Fig. 11. Selected area of the city (a) as a drawn map and (b) in Google Maps.
Fig. 12. Results of the numbers of the “survived” drones in the cases when (a)
Fig. 13. Results of the number of required steps to reach the destination in the cases when (a)
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Didar Yedilkhan, Abzal E. Kyzyrkanov, Zarina A. Kutpanova, Shadi Aljawarneh, Sabyrzhan K. Atanov. Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones[J]. Journal of Electronic Science and Technology, 2024, 22(4): 100277
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Received: May. 12, 2024
Accepted: Aug. 14, 2024
Published Online: Jan. 23, 2025
The Author Email: Kyzyrkanov Abzal E. (abzzall@gmail.com)