GEZGİN ROBOTLARIN İÇ ORTAMDA SEYRÜSEFERİ İÇİN SIKI BAĞLI BİR BAŞ AÇISI VE KONUMLANDIRMA SİSTEMİ

Bu çalışma, veri tümleştirme tekniklerinin, konumlandırma sistemlerinde gürbüz baş açısı ve konum bilgisi elde etmede etkinliğini göstermektedir. Önerilen system, gezgin robotun mutlak ve bağıl konumlandırma alt sistemlerini kullanarak baş açısı ve konum hesaplayan sıkı bağlı bir yapıya sahiptir. Bağıl konumlandırma alt sistemi, robotun odometre bilgilerini ve kinematik modelini kullanarak baş açısı ve konum bilgilerini elde eder. Mutlak konumlandırma sistemi ise, ultrasonik sinyalleri kullanarak konum ve aba baş açısı bilgisi elde etmektedir. Bu çalışmada, ilk olarak mutlak ve bağıl baş açısı bilgileri, geleneksel Kalman Filtresi ile tümleştirilerek gürbüz baş açısı bilgisi hesaplanmıştır. Daha sonra, bu gürbüz baş açısı bilgisi kullanılarak, bağıl konum ölçümünde düzeltme yapılmıştır. Son olarak, daha iyi konum bilgisi için, mutlak konum ve düzeltilmiş bağıl konumu tümleştirmek için uyarlanabilir bir Kalman filtresi uygulanmıştır. Deneysel çalışmada, sistemin konumsal doğruluğu ve hassasiyeti, test ortamı için sırasıyla 63 mm ve % 86 (konum hatası <100mm için) olarak elde edilmiştir. Önerilen sistem daha güvenilir, sürekli ve daha az gürültülü baş açısı ve konum bilgisi vermekte olup iç ortamlardaki birçok görev için uygundur.

A TIGHTLY COUPLED HEADING AND POSITIONING SYSTEM FOR INDOOR NAVIGATION OF MOBILE ROBOTS

This study shows the effectiveness of data fusion techniques to achieve robust heading and position information in localization systems. The proposed system that has tightly coupled structure calculates heading and position of the mobile robot using the absolute and relative positioning subsystems. The relative positioning subsystem obtains heading and position information by using the odometry information and kinematic model of the robot. Absolute positioning subsystem, calculates position and rough heading information using ultrasonic signals. In this study, firstly the robust heading information is calculated by combining absolute and relative heading with conventional Kalman Filter. And then the correction on the relative position measurement has been made by using this robust heading information. Finally, in order to better positional information, an adaptive Kalman filter is applied for fusing the the absolute position and the corrected relative position. In the experimental study, the positional accuracy and precision of the system is obtained as 63 mm and 86% (for positional error<100mm) respectively for the test environment. The proposed system gives more reliable, continuous and less noisy heading and position information and is suitable for many tasks in indoor environments.

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Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi-Cover
  • Yayın Aralığı: Yılda 3 Sayı
  • Başlangıç: 1986
  • Yayıncı: Eskişehir Osmangazi Üniversitesi