Automatic Guidance Algorism Based on Sensor Fusion of Geomagnetic Direction Sensor and Gyroscope. (Part 1). Sensor fusion composed of Kalman filter.

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  • MIZUSHIMA Akira
    The Japanese Society of Agricultural Machinery School of Agriculture, Graduate School of Hokkaido University
  • NOGUCHI Noboru
    The Japanese Society of Agricultural Machinery School of Agriculture, Graduate School of Hokkaido University
  • ISHII Kazunobu
    The Japanese Society of Agricultural Machinery School of Agriculture, Graduate School of Hokkaido University
  • TERAO Hideo
    The Japanese Society of Agricultural Machinery School of Agriculture, Graduate School of Hokkaido University
  • YUKUMOTO Osamu
    The Japanese Society of Agricultural Machinery Bio-oriented Technology Research Advancement Institution Present address: Agricultural Research Organization
  • YAMAMOTO Satoshi
    The Japanese Society of Agricultural Machinery Bio-oriented Technology Research Advancement Institution

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Other Title
  • 地磁気方位センサとジャイロスコープの航法センサ複合化による自動直進アルゴリズム　（第１報）　　カルマンフィルタによるセンサフュージョン
  • チジキ ホウイ センサ ト ジャイロスコープ ノ コウホウ センサ フクゴウカ ニ ヨル ジドウ チョクシン アルゴリズム ダイ1ポウ カルマン フィルタ ニ ヨル センサフュージョン
  • Sensor fusion composed of Kalman filter
  • カルマンフィルタによるセンサフュージョン

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The objective of this research is to develop an automatic guidance system composed of relatively low cost sensors. As a navigation sensor, we used a geomagnetic direction sensor (GDS) and a gyroscope. To increase the accuracy of these sensors outputs and guidance performance, these sensor output were integrated by sensor fusion technique. In the paper, a fiber optic gyroscope (FOG) was applied as a gyroscope. To evaluate the performance of these sensors for utilizing on an automatic guidance, and to confirm the effect of sensor fusion technique, the automatic guidance test was conducted on a paddy field. A kalman filter was employed as sensor fusion method. The kinematics of a vehicle was modeled and a heading error and a lateral offset were estimated by the kalman filter. The developed fusion technique was able to control the vehicle automatically with higher accuracy compared to that using single navigation sensor.

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