Neural Network Based Steering Controller for Vehicle Navigation on Sloping Land
スポンサーリンク
概要
- 論文の詳細を見る
This paper presents an autonomous guidance system of a wheeled tractor-like-robot on sloping terrain. A Neural Network (NN) vehicle model was developed for sloping land and trained using Back Propagation algorithm. Genetic algorithms were used to search the optimal steering values for different combinations of lateral and heading deviations. Using those values, a NN-based steering controller model was designed to generalize the optimal steering for different land-inclinations. Autonomous travel tests were conducted with a prototype test tractor along predetermined rectangular paths on sloping lands. It was found that the tractor could precisely follow the paths. The mean and standard deviation of the offsets along four linear directions of the rectangular path on 15° sloping land were 0.058 m and 0.063 m respectively, which are insignificant for tractor motion on agricultural farms.
論文 | ランダム
- A Color Holographic Reconstruction System by Time Division Multiplexing with Reference Lights of Laser
- 超仮想空間設計に関する一考察(画像技術・視覚・その他一般)
- IFDMAにおける適応的チャネル推定値選択による復調精度の改善 (無線通信システム)
- IFDMAにおける適応的チャネル推定値選択による復調精度の改善 (信号処理)
- B-5-111 次世代無線LANにおけるDCTを用いるCSIフィードバック法(B-5.無線通信システムB(無線アクセスネットワーク),一般セッション)