九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
九州大学大学院農学研究院生産環境科学部門生物生産工学分野
Laboratory of Bioproduction Engineering, Department of Bioproduction Environment Science, Faculty of Agriculture, Kyushu University
On traveling agricultural autonomous vehicle, when there are nonlinear factors in traveling, it is difficult to control the travel with this information. In this study, requisite traveling data such this information was verified under straight traveling in field. Then, NN was applied in order to be available for this data by controlling nonlinear factors at that time. Furthermore, the availability of NN to nonlinear factors was inspected through comparison between output from left and right wheel (before learning by NN) and learned output (after learning by NN). As a result, it was shown that absorbing nonlineal factors by NN is effective.
Mendeley出力
