Purpose: The purpose of this paper is the presentation and research of a novel robot vision system, which uses laser dynamic triangulation, to determine three-dimensional (3D) coordinates of an observed object. The previously used physical operation principle of discontinuous scanning method is substituted by continuous method. Thereby applications become possible that were previously limited by this discretization. Design/methodology/approach: The previously used prototype No. 2, which uses stepping motors to realize a discontinuous laser scan, was substituted by the new developed prototype No. 3, which contains servomotors, to achieve a continuous laser scan. The new prototype possesses only half the width and turns out to be significantly smaller and therefore lighter than the old one. Furthermore, no transmissions are used, which reduce the systematic error of laser positioning and increase the system reliability. Findings: By using a continuous laser scan method instead of discontinuous laser scan method, dead zones in the laser scanner field can be eliminated. Thereby, also by changing the physical operation principle, the implementation of applications is allowed, which previously was limited by the fixed step size or by the object distance under observation. By using servomotors instead of stepping motors, also a significant reduced positioning time can be accomplished maintaining the relative positioning error less than 1 per cent. Originality/value: The originality is based on the substitution of the physical operation principle of discontinuous by continuous laser scan. The previously used stepping motors discretized the laser scanner field and thereby produced dead zones, where 3D coordinates cannot be detected. These stepping motors were substituted by servomotors to revoke these disadvantages and provide a continuous laser scan, where dead zones in the field of view get eliminated and the step response of the laser scanner accelerated.

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.

Camera-centric perception has matured into a cornerstone of modern autonomy, from self-driving cars and factory cobots to underwater and planetary exploration. This review synthesizes more than a decade of progress in vision-based robotic navigation through an engineering lens, charting the full pipeline from sensing to deployment. We first examine the expanding sensor palette—monocular and multi-camera rigs, stereo and RGB-D devices, LiDAR–camera hybrids, event cameras, and infrared systems—highlighting the complementary operating envelopes and the rise of learning-based depth inference. The advances in visual localization and mapping are then analyzed, contrasting sparse and dense SLAM approaches, as well as monocular, stereo, and visual–inertial formulations. Additional topics include loop closure, semantic mapping, and LiDAR–visual–inertial fusion, which enables drift-free operation in dynamic environments. Building on these foundations, we review the navigation and control strategies, spanning classical planning, reinforcement and imitation learning, hybrid topological–metric memories, and emerging visual language guidance. Application case studies—autonomous driving, industrial manipulation, autonomous underwater vehicles, planetary rovers, aerial drones, and humanoids—demonstrate how tailored sensor suites and algorithms meet domain-specific constraints. Finally, the future research trajectories are distilled: generative AI for synthetic training data and scene completion; high-density 3D perception with solid-state LiDAR and neural implicit representations; event-based vision for ultra-fast control; and human-centric autonomy in next-generation robots. By providing a unified taxonomy, a comparative analysis, and engineering guidelines, this review aims to inform researchers and practitioners designing robust, scalable, vision-driven robotic systems.

Mesostructured pillared zeolite materials in the form of lamellar phases with a crystal structure of mordenite (MOR) and ZSM-5 (MFI) were grown using CTAB as an agent that creates mesopores, in a one-pot synthesis; then into the CTAB layers separating the 2D zeolite plates were introduced by diffusion the TEOS molecules which were further hydrolyzed, and finally the material was annealed to remove the organic phase, leaving the 2D zeolite plates separated by pillars of silicon dioxide. To monitor the successive structural changes and the state of the atoms of the zeolite framework and organic compounds at all the steps of the synthesis of pillared MOR and MFI zeolites, the nuclear magnetic resonance method (NMR) with magic angle spinning (MAS) was applied. The ²⁷Al and ²⁹Si MAS NMR spectra confirm the regularity of the zeolite frameworks of the as synthetized materials. Analysis of the ¹H and ¹³C MAS NMR spectra and an experiment with variable contact time evidence a strong interaction between the charged “heads” –[N(CH₃)₃]⁺ of CTAB and the zeolite framework at the place of [AlO₄]⁻ location. According to ²⁷Al and ²⁹Si MAS NMR the evacuation of organic cations leads to a partial but not critical collapse of the local zeolite structure.