Abstract
The aim of this study was to design a navigation system composed of a human-controlled leader vehicle and a follower vehicle. The follower vehicle automatically tracks the leader vehicle. With such a system, a human driver can control two vehicles efficiently in agricultural operations. The tracking system was developed for the leader and the follower vehicle, and control of the follower was performed using a camera vision system. A stable and accurate monocular vision-based sensing system was designed, consisting of a camera and rectangular markers. Noise in the data acquisition was reduced by using the least-squares method. A feedback control algorithm was used to allow the follower vehicle to track the trajectory of the leader vehicle. A proportional–integral–derivative (PID) controller was introduced to maintain the required distance between the leader and the follower vehicle. Field experiments were conducted to evaluate the sensing and tracking performances of the leader–follower system while the leader vehicle was driven at an average speed of 0.3 m/s. In the case of linear trajectory tracking, the RMS errors were 6.5, 8.9, and 16.4 cm for straight, turning, and zigzag paths, respectively. Again, for parallel trajectory tracking, the root mean square (RMS) errors were found to be 7.1, 14.6, and 14.0 cm for straight, turning and zigzag paths, respectively. The navigation performances indicated that the autonomous follower vehicle was able to follow the leader vehicle, and the tracking accuracy was found to be satisfactory. Therefore, the developed leader–follower system can be implemented for the harvesting of grains, using a combine as the leader and an unloader as the autonomous follower vehicle.
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Acknowledgments
Thanks to Open Access Publishers Land from MDPI to have their policy to support the authors for reusing of the published article. In this regard, we would like to extend our gratitude to Sensors Journal to publish this article (Linhuan Zhang, Tofael Ahamed, Yan Zhang, Pengbo Gao and Tomohiro Takigawa. Vision-Based Leader Vehicle Trajectory Tracking for Multiple Agricultural Vehicles. Sensors, 16(4), 578; https://doi.org/10.3390/s16040578, 2016). We thank University of Tsukuba for supporting this research and express our gratitude to the technical staff of Agricultural and Forest Research Center, University of Tsukuba for their cooperation.
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Zhang, L., Ahamed, T., Zhang, Y., Gao, P., Takigawa, T. (2023). Vision-Based Leader Vehicle Trajectory Tracking for Multiple Agricultural Vehicles. In: Ahamed, T. (eds) IoT and AI in Agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-19-8113-5_16
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