To better control the growing process of horticulture plants greenhouse growers need an automated way to efficiently and effectively find where diseases are spreading.The HiPerGreen project has done research in using an autonomous quadcopter for this scouting. In order for the quadcopter to be able to scout autonomously accurate location data is needed. Several different methods of obtaining location data have been investigated in prior research. In this research a relative sensor based on optical flow is looked into as a method of stabilizing an absolute measurement based on trilateration. For the optical flow sensor a novel block matching algorithm was developed. Simulated testing showed that Kalman Filter based sensor fusion of both measurements worked to reduce the standard deviation of the absolute measurement from 30 cm to less than 1 cm, while drift due to dead-reckoning was reduced to a maximum of 11 cm from over 36 cm.
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In this paper, we experimentally compare orthogonal frequency-division multiplexing (OFDM) and on-off keying (OOK) modulation in the context of the IEEE 802.15.13-2023 standard at bandwidths up to 50 MHz across a Li-Fi link with distances up to 5 m and a lateral offset up to 51°. Error vector magnitude (EVM) and bit error rate (BER) evaluations confirm that the high peak-to-average power ratio (PAPR) of OFDM limits the achievable transmission distance, but it offers higher data rates due to its higher spectral efficiency. Due to the lower PAPR, OOK-based Pulsed Modulation PHY (PM-PHY) shows a significantly higher link range. As the structure of the PM-PHY is based on OFDM symbols, the two solutions may also be combined to open a wider range of use cases for optical wireless communications.
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This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
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