Abstract
People gain a physical sense of the environment surrounding them via visual information from the eyes; but from these observations alone we are not capable of determining the exact dimensions of the environment. Field robots use sensors such as Global Position System (GPS) or Inertial Measurement Units (IMU) to make accurate estimations of the position and attitude, but these instruments cannot provide accurate relative measurements with respect to a specific site without prior surveying. Computer vision techniques, i. e. using cameras as sensors; offer vision information that gives a physical sense of a robotic platform pose with respect to some targeted site, and are capable of making accurate estimates of relative positions and attitudes.
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Tsai, A., Gibbens, P., Hugh Stone, R. (2008). Visual Position Estimation for Automatic Landing of a Tail-Sitter Vertical Takeoff and Landing Unmanned Air Vehicle. In: Billingsley, J., Bradbeer, R. (eds) Mechatronics and Machine Vision in Practice. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74027-8_14
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DOI: https://doi.org/10.1007/978-3-540-74027-8_14
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