選択的不感化ニューラルネットを用いた教師あり学習による自律移動ロボットのナビゲーション

Key Points

• To enhance navigation flexibility of outdoor autonomous robots through efficient supervised learning.
• Utilized selective neural networks for navigation tasks.
• Incorporated sensor information for real-time learning.
• Linked operator intuition with robot responses.
• Assessed performance in various courses.
• Achieved stable navigation across multiple courses.
• Demonstrated high accuracy with efficient learning methods.