International Journal For Multidisciplinary Research

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Enhancing Autonomous Drones With Self- Designed Payload Dropping Mechanism

Author(s) Urmit Singh, Nikul Kumar, Peeyush Chauhan
Country India
Abstract This research paper provides a comprehensive exploration of an autonomous drone experiment integrating the Pixhawk 2.4.8 flight controller. The study offers a detailed analysis of a drone system characterized by a 200-gram payload capacity and a maximum flight duration of 13 minutes. The CAD model, meticulously designed using Dassault's SolidWorks Design Tool, incorporates carbon fiber propellers to optimize both durability and flexibility. One noteworthy contribution of this research is the introduction of a self-designed payload deployment mechanism, further extending the drone's capabilities. Additionally, specialized landing equipment is developed to enhance takeoff and landing stability, thereby elevating overall system performance. The study emphasizes the drone's precise control and navigation capabilities, made possible by its robust processing capacity and integrated sensors. Leveraging the computational prowess of the Raspberry Pi 4B, this project efficiently manages complex algorithms crucial for autonomous operations, all while maintaining cost-effectiveness. The Raspberry Pi's high-resolution capabilities and seamless integration prove to be the optimal choice for accurate object detection, environmental recognition, autonomous navigation, and successful payload deployment missions. This research contributes valuable insights into the integration of advanced technologies in autonomous drone systems, with a particular focus on enhancing their capabilities through self-designed payload deployment mechanisms.
Keywords Drone, innovative design, CAD, FEA, payload mechanism
Field Engineering
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-11-20
Cite This Enhancing Autonomous Drones With Self- Designed Payload Dropping Mechanism - Urmit Singh, Nikul Kumar, Peeyush Chauhan - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.9242
DOI https://doi.org/10.36948/ijfmr.2023.v05i06.9242
Short DOI https://doi.org/gs5mfh
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