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  • 1.
    Ericson, Stefan K.
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Åstrand, Björn S.
    School of Information Science, Computer and Electrical Engineering, Halmstad University, Halmstad, Sweden.
    Analysis of two visual odometry systems for use in an agricultural field environment2018In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 166, p. 116-125Article in journal (Refereed)
    Abstract [en]

    This paper analyses two visual odometry systems for use in an agricultural field environment. The impact of various design parameters and camera setups are evaluated in a simulation environment. Four real field experiments were conducted using a mobile robot operating in an agricultural field. The robot was controlled to travel in a regular back-and-forth pattern with headland turns. The experimental runs were 1.8–3.1 km long and consisted of 32–63,000 frames. The results indicate that a camera angle of 75° gives the best results with the least error. An increased camera resolution only improves the result slightly. The algorithm must be able to reduce error accumulation by adapting the frame rate to minimise error. The results also illustrate the difficulties of estimating roll and pitch using a downward-facing camera. The best results for full 6-DOF position estimation were obtained on a 1.8-km run using 6680 frames captured from the forward-facing cameras. The translation error (x,y,z) is 3.76% and the rotational error (i.e., roll, pitch, and yaw) is 0.0482 deg m−1. The main contributions of this paper are an analysis of design option impacts on visual odometry results and a comparison of two state-of-the-art visual odometry algorithms, applied to agricultural field data.

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