Free-space optical communication has the potential to transmit information with both high speed and security. However, since it is unguided it suffers from losses due to atmospheric turbulence and diffraction. To overcome the diffraction limits the long-distance propagation of Bessel beams is considered and compared against Gaussian beam properties. Bessel beams are shown to have a number of benefits over Gaussian beams when propagating through atmospheric turbulence.

This article proposes an adaptive neuro-fuzzy inference system (ANFIS) for solving navigation problems of an autonomous ground vehicle (AGV). The system consists of four ANFIS controllers; two of which are used for regulating both the left and right angular velocities of the AGV in order to reach the target position; and other two ANFIS controllers are used for optimal heading adjustment in order to avoid obstacles. The two velocity controllers receive three sensor inputs: front distance (FD); right distance (RD) and left distance (LD) for the low-level motion control. Two heading controllers deploy the angle difference (AD) between the heading of AGV and the angle to the target to choose the optimal direction. The simulation experiments have been carried out under two different scenarios to investigate the feasibility of the proposed ANFIS technique. The simulation results have been presented using MATLAB software package; showing that ANFIS is capable of performing the navigation and path planning task safely and efficiently in a workspace populated with static obstacles.

An optimal control technique is proposed to address the problem of path tracking of an autonomous ground vehicle. This technique utilizes a Fractional Order Proportional Integral Derivative (FOPID) controller to control a non-holonomic autonomous ground vehicle to track the behaviour of the predefined reference path. Two FOPID controllers are designed to control the vehicle's inputs. These inputs represent the torques that are used in order to manipulate the implemented model of the vehicle to obtain the actual path. The implemented model of the non-holonomic autonomous ground vehicle takes into consideration both of the kinematic and dynamic models. In additional, a Particle Swarm Optimization (PSO) algorithm is used to optimize the FOPID controllers' parameters. These optimal tuned parameters of FOPID controllers minimize the cost function used in the algorithm. The effectiveness and validation of the proposed method have been verified through different patterns of reference paths using MATLAB-SIMULINK software package. The newly obtained results of FOPID controller show the advantage and the performance of the technique in terms of minimizing path tracking error and the complement of the path following.

A new stereophotolithography technique utilizing a spatial light modulator (SLM) to create three-dimensional components with a planar, layer-by-layer process of exposure is described. With this procedure it is possible to build components with dimensions in the range of 50 μm–50 mm and feature sizes as small as 5 μm with a resolution of 1 μm. A polysilicon thin-film twisted nematic SVGA SLM is used as the dynamic photolithographic mask. The system consists of eight elements: a UV laser light source, an optical shutter, beam-conditioning optics, a SLM, a multielement reduction lens system, a high-resolution translation stage, a control system, and a computer-aided-design system. Each of these system components is briefly described. In addition, the optical characteristics of commercially available UV curable resins are investigated with nondegenerate four-wave mixing. Holographic gratings were written at a wavelength of 351.1 nm and read at 632.8 nm to compare the reactivity, curing speed, shrinkage, and resolution of the resins. These experiments were carried out to prove the suitability of these photopolymerization systems for microstereolithography.