Purpose: The purpose of this paper is to present a novel application for a newly developed Technical Vision System (TVS), which uses a laser scanner and dynamic triangulation, to determine the vitality of agriculture vegetation. This vision system, installed on an unmanned aerial vehicle, shall measure the reflected laser energy and thereby determine the normalized differenced vegetation index. Design/methodology/approach: The newly developed TVS shall be installed on the front part of the unmanned aerial vehicle, to perform line-by-line scan in the vision system field-of-view. The TVS uses high-quality DC motors, instead of previously researched low-quality DC motors, to eliminate the existence of two mutually exclusive conditions, for exact positioning of a DC motor shaft. The use of high-quality DC motors reduces the positioning error after control. Findings: Present paper emphasizes the exact laser beam positioning in the field-of-view of a TVS. By use of high-quality instead of low-quality DC motors, a significant reduced positioning time was achieved, maintaining the relative angular position error less than 1 per cent. Best results were achieved, by realizing a quasi-continuous control, using a high pulse-width modulated duty cycle resolution and a high execution frequency of the positioning algorithm. Originality/value: The originality of present paper is represented by the novel application of the newly developed TVS in the field of agriculture. The vitality of vegetation shall be determined by measuring the reflected laser energy of a scanned agriculture zone. The paper’s main focus is on the exact laser beam positioning within the TVS field-of-view, using high-quality DC motors in closed-loop position control configuration.

Optical images and signals can be used to detect displacement in civil engineering structures. This paper presents a technical experimentation of a vision‐based technology and artificial intelligence algorithms methodology for structural health monitoring of new and aging structures, by a noncontact and nondestructive system. The experimental study emphasis is on the outdoor urban environment, by the detection of spatial coordinate displacement on the structures, in order to perform a damage assessment. Also, the experimental study contains both theoretical and experimental aspects of the fusion of image and range scanner datasets created using intelligent algorithms. A camera and an optical scanning system were used to generate high resolution and quality images for 2D imaging, and 3D accuracy range data from optoelectronic sensor signals. Scans at a specific area of an engineering structure were performed to measure spatial coordinates displacements, successfully verifying the effectiveness and the robustness of the proposed non‐contact and non‐destructive monitoring approach.

This paper presents a technical vision system designed to resolve multiple tasks which are fundamental for autonomous navigation. These tasks include detecting the presence of a significant obstacle for a mobile robot, locate its position in the mobile robot's field of view and create a digital map of the obstacle's visible surface with metrological accuracy. This technical vision system has been introduced and explained in other publications; therefore this paper focuses mostly on signal conditioning, processing and resolution increase for mobile robot navigation.