Route following based on visual landmark matching may require many models to cover all different situations. This paper describes a system that is able to adapt template's modelling parameters to environmental conditions (lighting, shadows, etc.) by a genetic learning technique. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence problem in the 3D position estimation. The experimental results show that the tracking robustness is improved, while using a small set of templates. © 1998 Elsevier Science B.V. All rights reserved.
Zingaretti P., Carbonaro A. (2004). Route following based on adaptive visual landmark matching. ROBOTICS AND AUTONOMOUS SYSTEMS, 25(3-4), 177-184 [10.1016/S0921-8890(98)00047-5].
Route following based on adaptive visual landmark matching
Carbonaro A.
2004
Abstract
Route following based on visual landmark matching may require many models to cover all different situations. This paper describes a system that is able to adapt template's modelling parameters to environmental conditions (lighting, shadows, etc.) by a genetic learning technique. In addition, the mobile robot self-localisation is obtained by a stereo approach that uses the centres of matching in the two images to solve in a simple way the correspondence problem in the 3D position estimation. The experimental results show that the tracking robustness is improved, while using a small set of templates. © 1998 Elsevier Science B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
