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Vision in indoor and outdoor drones

Vision in indoor and outdoor drones

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This chapter explores how the type of environmental impacts the CV techniques, algorithms and specific hardware to be used. Indoor environments, also known as controlled environments, generally rely on solutions based on beacons, proximity sensors and image processing for data acquisition. In this case, as the environment is controlled, the illuminance of the scene is adjusted and sensors are previously positioned, which facilitates the development and execution of these systems. In outdoor environments, generally known for uncontrolled environmental variables, frequently require solutions based on image processing techniques to provide the data acquisition. In this environment, the non-constant variation of the illuminance of the scene and the great variation of the background of images are important complicating factors for the operation of the image processing algorithms. In addition, constructions and buildings block the signal of sensors and global positioning systems making it even harder to treat the exceptions caused by these factors. Each exception being treated in a CV system has a computational cost that can be high. If this is considered in applications using embedded hardware, some projects simply become infeasible. Researchers put great effort attempting to optimise the software for high performance and better use of the hardware resources, so that less processing power is demanded as well as positively impacting the energy savings. This chapter presents a review of the main CV techniques currently used in the development of mission control software for the use in indoor and outdoor environments, providing autonomy navigation and interaction for these aerial robots.

Chapter Contents:

  • 11.1 Computer vision in unmanned aerial vehicles
  • 11.1.1 Indoor environments
  • 11.1.2 Outdoor environments
  • 11.2 Other approaches handling both indoor and outdoor environments
  • 11.3 Conclusion
  • References

Inspec keywords: robot vision; indoor environment; software engineering; autonomous aerial vehicles

Other keywords: data acquisition; controlled environments; outdoor drones; beacons; outdoor environments; indoor drones; global positioning systems; proximity sensors; mission control software development; aerial robots; hardware resources; image processing algorithms; CV techniques; environmental impacts; indoor environments; CV system

Subjects: Mobile robots; Optical, image and video signal processing; Software engineering techniques; Computer vision and image processing techniques; Telerobotics

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