engleski

Experimental Evaluation of Autonomous Driving Based on Visual Memory and Image Based Visual Servoing

In this paper, the performance of a topological- metric visual path following framework is investigated in different environments. The framework relies on a monocular camera as the only sensing modality. The path is represented as a series of reference images such that each neighboring pair contains a number of common landmarks. Local 3D geometries are reconstructed between the neighboring reference images in order to achieve fast feature prediction. This allows recovery from tracking failures. During navigation the robot is controlled using image-based visual servoing. The focus of the paper is on the results from a number of experiments conducted in different environments, lighting conditions and seasons. The experiments with a robot-car show that the framework is robust against moving objects and moderate illumination changes. It is also shown that the system is capable of on-line path learning.

visual servoing; mapping; localization; visual memory; path following

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