Benda Referensi sebagai Acuan Penyederhanaan untuk Deteksi Benda pada Kondisi Terhalang dengan Metoda Support Machine
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Abstract
Object in an unobstructed condition is a very difficult condition to recognize. This is due to the overall size of imperfect objects visible. For robot applications, of course this will be very annoying. This condition will lead to errors in decision-making for robots. On the other hand, the crowd of objects that are too much in the robot work environment will complicate the robot in executing objects desired by the user. Robot will easily recognize the object if the object is in a limited environment and not too much so that the focus of his work is more optimal. On too many objects, the probability of the target object will decrease as the number of other objects also allows becoming the candidate as the target object. For that we need an effort to simplify the work environment of the robot so that the focus can be more focused by dividing the environment that is too crowded into several parts. One of the benchmarks in dividing the environment is a reference object. This research will focus on the discussion and the role of reference objects to simplify the environment that is too complicated for robot work. The reference object will be determined by the robot itself from the features with predefined parameters. An important point in this research is how robots can be as intelligent as humans think in determining what references object criteria are used. As cluster determination for reference object used support vector machine method as guide of robot determine class and feature object. The desired end goal is the formation of a simple system in the robot, Simple in this sense is the maximum number of objects 3 pieces.
Keywords : object detection, support vector machine, reference object
Abstrak— Sebuah benda dalam kondisi terhalang, merupakan kondisi yang sangat sulit untuk dikenali. Hal ini disebabkan keseluruhan bentuk benda tidak sempurna terlihat. Untuk aplikasi robot, tentu saja hal ini akan sangat mengganggu. Benda yang tidak sempurna terlihat akan menimbulkan kesalahan pada pengambilan keputusan bagi robot. Di sisi lain, kerumunan benda yang terlalu banyak pada lingkungan kerja robot, akan menyulitkan robot dalam mengeksekusi benda yang diinginkan oleh pengguna. Robot akan mudah mengenali benda apabila benda tersebut berada pada lingkungan yang terbatas dan tidak terlalu banyak sehingga fokus kerja nya lebih optimal. Pada benda yang terlalu banyak, probabilitas benda sasaran akan semakin kecil karena banyaknya benda-benda lain yang memungkin juga untuk menjadi kandidat sebagai benda sasaran. Untuk itu diperlukan suatu upaya menyederhanakan lingkungan kerja robot agar fokusnya bisa lebih terarah dengan cara membagi lingkungan yang terlalu ramai tersebut menjadi beberapa bagian. Salah satu patokan dalam membagi lingkungan tersebut adalah benda referensi. Penelitian ini akan menitik beratkan pada pembahasan dan peran benda referensi untuk menyederhanakan lingkungan yang terlalu ramai bagi kerja robot. Benda referensi akan ditentukan oleh robot sendiri dari fitur –fitur benda dengan parameter-parameter yang telah ditentukan. Point penting dalam penelitian ini adalah bagaimana robot bisa dengan cerdas dalam menentukan kriteria benda referensi apa yang digunakan. Sebagai penentuan kluster untuk benda referensi digunakan metoda support vector machine sebagai panduan robot menentukan kelas dan fitur benda. Tujuan akhir yang diinginkan adalah terbentuknya sistem yang sederhana dalam padangan robot, Sederhana dalam pengertian ini adalah jumlah benda maksimal 3 buah.
Kata Kunci : deteksi benda, support vector machine. benda referensi
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Rahmadi Kurnia, Universitas Andalas
Rahmadi Kurnia menyelesaikan pendidikan Sarjana Teknik dan Magister Teknik di Universitas Indonesia tahun 1995 dan 1998. Gelar Dr Eng diperolehnya dari Saitama University, Jepang. Saat ini bekerja sebagai staff pengajar di Jurusan Teknik Elektro Universitas Andalas.
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