Adaptive Autonomous Technology in Unmanned Aerial Vehicles for Parcel Delivery

Authors

  • Thamma Bhanu Sumanth Reddy  Department of Computer Science and Engineering, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • Pullagura Harsha Teja  Department of Computer Science and Engineering, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • Regalla Pavan Teja  Department of Computer Science and Engineering, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India
  • Thandra Praneeth  Department of Computer Science and Engineering, Vasireddy Venkatadri Institute of Technology, Guntur, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/CSEIT1951138

Keywords:

Autonomous, Collision Avoidance, Delivery Service, Flight modes, Hexa copter, Navigation, Detect and Avoid.

Abstract

An Unmanned Aerial Vehicle (often called a Drone) is an aircraft that is not operated by a pilot on board. Drones are rapidly growing market and increasingly leverage. The Applications of these flying robots are limitless. This paper reviews and discusses about embedded vision and sensor technology which culminates in several innovative applications over drones. It introduces an industry alliance available to help product creators incorporate robust vision capabilities into their drones designs.This paper mainly deals on Autonomous Delivery of light weighted items along with the collision avoidance technology and also tracks the whereabouts of the vehicle in a cost effective approach. This can also be used for carrying out complex assignments such as rescue operations during disasters, mines surveying.

References

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Published

2019-03-30

Issue

Section

Research Articles

How to Cite

[1]
Thamma Bhanu Sumanth Reddy, Pullagura Harsha Teja, Regalla Pavan Teja, Thandra Praneeth, " Adaptive Autonomous Technology in Unmanned Aerial Vehicles for Parcel Delivery, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.07-12, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT1951138