Trajectory prediction of moving objects by means of neural networks
Barışık, Hakan.

Trajectory prediction of moving objects by means of neural networks

Barışık, Hakan.

Yazar Ek Girişi
Barışık, Hakan.

Yayın Bilgileri
[s.l.]: [s.n.], 1997.

Fiziksel Tanımlama
viii, 105 leaves.: ill.

Estimating the three-dimensional motion of an object from a sequence of object positions and orientation is of significant importance in variety of applications in control and robotics. For instance, autonomous navigation, manipulation, servo, tracking, planning and surveillance needs prediction of motion parameters. Although "motion estimation" is an old problem (the formulations date back to the beginning of the century), only recently scientists have provided with the tools from nonlinear system estimation theory to solve this problem eural Networks are the ones which have recently been used in many nonlinear dynamic system parameter estimation context. The approximating ability of the neural network is used to identifY the relation between system variables and parameters of a dynamic system. The position, velocity and acceleration of the object are estimated by several neural networks using the II most recent measurements of the object coordinates as input to the system Several neural network topologies with different configurations are introduced and utilized in the solution of the problem. Training schemes for each configuration are given in detail. Simulation results for prediction of motion having different characteristics via different architectures with alternative configurations are presented comparatively.

Konu Başlığı
Neural networks (Computer science)

Yazar Ek Girişi
Aytaç, Sıtkı.

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
İzmir Institute of Technology: Computer Engineering--Thesis (Master).

Elektronik Erişim
Access to Electronic Version.

KütüphaneMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTETezT000034QA76.87 .B37 1997Tez Koleksiyonu