Aplikasi Reinforcement Learning Helikopter Aerobatik

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Referensi:
Abbeel P., Coates A., Quigley M., Ng A. Y. (2006). An application of reinforcement learning to aerobatic helicopter flight. Diakses tanggal 15 Juli 2017, dari http://www.cs.stanford.edu/~pabbeel/heli-nips2006.

Penerbangan helikopter secara (autonomus helicopter flight) secara umum dianggap sarat dengan masalah kesulitan di dalam mengendalikan pengoperasiannya. Penelitian ini menyajikan pembahasan tentang keberhasilan di dalam mengoperasikan helikopter yang dikendalikan dari jarak jauh (RC helicopter) dengan empat gerakan manuver yang berbeda, yakni flip ke depan (forward flip), berputar ke samping (sideways roll) pada kecepatan rendah, tail-in funnel, dan nose-in funnel. Hasil percobaan secara signfikan memperkaya kelebihan yang dimiliki sistem penerbangan helikopter otonom. Penelitian ini menggunakan sejumlah pendekatan. Pertama, percobaan helikopter yang dikemudikan oleh seorang pilot untuk membantu pengamatan mengenai model dinamika dan fungsi imbalan (biaya). Kedua, penggunaan algoritma reinforcement learning (kendali optimal) untuk menemukan controller yang dioptimalkan untuk menghasilkan model dan fungsi imbalan. Ketiga, pemrograman dinamika diferensial (differential dynamic programming, atau DDP) yang merupakan pengembangan dari regulator kuadrat linier (linear quadratic regulator, atau LOR).

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