Development of trajectory prediction program for a moving object in 3D environment = Pengembangan program trajectory prediction dalam koordinat 3 dimensi
Hoo Kevin Wijaya;
Wahidin Wahab, supervisor; Benyamin Kusumoputro, examiner; Abdul Mun`is, co-promotor
([, ], 2015)
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[Teknologi robot yang berkembang pesat sekarang ini menyebabkannaiknya kebutuhan akan teknik pengolahan citra dan teknik memprediksi gerakobjek. Salah satu cara yang paling umum dalam mendeteksi suatu benda adalahdengan menggunakan filter warna dan sensor untuk mendeteksi jarak. Namun,kelemahan metode tersebut terletak pada rentannya filter warna terhadapgangguan luar, serta lambatnya sensor dalam mengukur jarak. Dalam penelitianini, digunakan sebuah Kalman Filter yang berfungsi untuk mengurangi efekgangguan dalam filter warna, serta membuat program tetap dapat memprediksilokasi bola ketika bola hilang dari pandangan. Sebuah algoritma yang dapatmemprediksi jarak dan koordinat bola tanpa menggunakan sensor jugadikembangkan demi mempercepat waktu proses. Setelah lokasi bola diketahui,sebuah algoritma untuk memprediksi koordinat jatuh bola juga dikembangkan.Koordinat jatuh ini nantinya dapat dimasukkan ke sistem penggerak robot yangmampu mengarahkan robot ke lokasi jatuhnya benda.;Image processing and trajectory prediction play an important role in today?srobotic technology and its applications are limitless. The most common method ofdetecting an object is through the use of colour filter and a sensor to measure itsdistance. However, most of the time, colour filter is very vulnerable to noise andthe robot would consume a huge chunk of processing time using distance sensor.In this paper, a Kalman Filter is developed base on a constant velocity model.This Kalman Filter will provide a better estimator on the object?s position andestimate the position of the object when there are occlusions. In addition to theKalman Filter, a novel sensorless approach to measure an object?s distance is alsodeveloped in order to improve processing time. After the coordinates of the objectare obtained, an algorithm that could predict its landing coordinates is alsodeveloped by using MATLAB. This landing coordinates could then be fed into amotor system in a robot which will then move towards the predicted coordinates., Image processing and trajectory prediction play an important role in today’srobotic technology and its applications are limitless. The most common method ofdetecting an object is through the use of colour filter and a sensor to measure itsdistance. However, most of the time, colour filter is very vulnerable to noise andthe robot would consume a huge chunk of processing time using distance sensor.In this paper, a Kalman Filter is developed base on a constant velocity model.This Kalman Filter will provide a better estimator on the object’s position andestimate the position of the object when there are occlusions. In addition to theKalman Filter, a novel sensorless approach to measure an object’s distance is alsodeveloped in order to improve processing time. After the coordinates of the objectare obtained, an algorithm that could predict its landing coordinates is alsodeveloped by using MATLAB. This landing coordinates could then be fed into amotor system in a robot which will then move towards the predicted coordinates.] |
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No. Panggil : | S62275 |
Entri utama-Nama orang : | |
Entri tambahan-Nama orang : | |
Entri tambahan-Nama badan : | |
Subjek : | |
Penerbitan : | [Place of publication not identified]: [, ], 2015 |
Program Studi : |
Bahasa : | eng |
Sumber Pengatalogan : | LibUI eng rda |
Tipe Konten : | text |
Tipe Media : | unmediated ; computer |
Tipe Carrier : | volume ; online resource |
Deskripsi Fisik : | x, 67 pages : illustration ; 30 cm + appendix |
Naskah Ringkas : | |
Lembaga Pemilik : | Universitas Indonesia |
Lokasi : | Perpustakaan UI, Lantai 3 |
No. Panggil | No. Barkod | Ketersediaan |
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S62275 | 14-18-281830660 | TERSEDIA |
Ulasan: |
Tidak ada ulasan pada koleksi ini: 20421230 |