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Modern service robots are designed to work in a complex indoor environment, in which the robot has to interact with the objects in different ambient light intensities (day light, tube light, halogen light and dark ambiance). The variations in sudden ambient light intensities often cause an error in the sensory information of optical sensors like laser scanner, which reduce the reliability of the sensor in applications such as mapping, path planning and object detection of a mobile robot. Laser scanner is an optical sensor, so sensory information depends upon parameters like surface reflectivity, ambient light condition, texture of the targets, etc. The purposes of this research are to investigate and remove the effect of variation in ambient light conditions on the laser scanner to achieve robust autonomous mobile robot navigation.

The objective of this study is to analyze the effect of ambient light condition (dark ambiance, tube light and halogen bulb) on the accuracy of the laser scanner for the robust autonomous navigation of mobile robot in diverse illumination environments. A proposed AIFA (Adaptive Intensity Filter Algorithm) approach is designed in robot operating system (ROS) and implemented on a mobile robot fitted with laser scanner to reduce the effect of high-intensity ambiance illumination of the environment.

It has been experimentally found that the variation in the measured distance in dark is more consistent and accurate as compared to the sensory information taken in high-intensity tube light/halogen bulbs and in sunlight. The proposed AIFA approach is implement on a laser scanner fitted on a mobile robot which navigates in the high-intensity ambiance-illuminating complex environment. During autonomous navigation of mobile robot, while implementing the AIFA filter, the proportion of cession with the obstacles is reduce to 23 per cent lesser as compared to conventional approaches.

The proposed AIFA approach reduced the effect of the varying ambient light conditions in the sensory information of laser scanner for the applications such as autonomous navigation, path planning, mapping, etc. in diverse ambiance environment.

THE British Committee was formed in June, 1929, in compliance with the recommendations of the International Commission on Illumination when at Saranac, New York, U.S.A., in September, 1928. This Committee was representative of all the interests connected with civil aviation, including the Air Ministry, the operating companies and the manufacturers of aviation equipment. In view of the novelty of the subject, it was felt that a paper collecting the data which had been discussed by the Committee during its numerous meetings, and also discussing the fundamental considerations which have to be borne in mind in designing equipment, would not be without value.

UV light curing of adhesives has become the method of choice for many more industrial bonding, sealing, coating, potting and tacking applications. Because faster cures provide more efficient manufacturing processes and lower total assembly cost, and because light curing adhesives are being used in more kinds of applications, both the range of resins and curing equipment now available has expanded dramatically. Outlines the performances of currently available UV adhesives, their application and selection of UV light sources.

One of the problems with curing films containing a titanium pigment with ultraviolet light is the rapid attenuation of the incident light by the pigment. This limits both the pigmentation level and the thickness of film that can be effectively cured. In this study, the transmission by thin pigmented films of light of wavelength in the range 320–400 nm is measured experimentally. It is shown that the massive absorption of both the rutile and anatase forms of titanium dioxide in this region is responsible for the rapid attenuation of the light used to cure the films. The principal conclusion is that, given a constant lamp intensity and photoinitiator efficiency, the larger the wavelength of the light used to cure the film the greater will be the thickness of film that can be cured.

Background subtraction is a particularly popular foreground detection method, whose background model can be updated by using input images. However, foreground object cannot be detected accurately if the background model is broken. In order to improve the performance of foreground detection in human-robot interaction (HRI), the purpose of this paper is to propose a new background subtraction method based on image parameters, which helps to improve the robustness of the existing background subtraction method.

The proposed method evaluates the image and foreground results according to the image parameters representing the change features of the image. It ignores the image that is similar to the first image and the previous image in image sequence, filters the image that may break the background model and detects the abnormal background model. The method also helps to rebuild the background model when the model is broken.

Experimental results of typical interaction scenes validate that the proposed method helps to reduce the broken probability of background model and improve the robustness of background subtraction.

Different threshold values of image parameters may affect the results in different environments. Future researches should focus on the automatic selection of parameters’ threshold values according to the interaction scene.

A useful method for foreground detection in HRI.

This paper proposes a method which employs image parameters to improve the robustness of the background subtraction for foreground detection in HRI.

Photoresist imaging traditionally uses silver halide or diazo based phototools for contact exposure to an actinic UV light source. By contrast, laser direct imaging uses digital imaging data to control a laser beam scanner to write directly on to the photoresist, therefore eliminating the need for phototools. In the past, even though the benefit of a UV system was recognised, laser direct imaging was mainly limited to the use of a visible laser as early UV lasers were low in power, unreliable and expensive. So far, no visible systems have gained commercial recognition because of the inherent deficiencies of the visible system. Recent advantages in UV laser equipment and UV sensitive photoresist have now made UV laser direct imaging a viable alternative to traditional contact imaging. As new UV laser imaging systems start to emerge, interest and attention are also growing among printed circuit board manufacturers. This paper discusses various attributes of a UV laser direct imaging system and fundamental differences in photophysics between laser direct imaging and conventional UV imaging.

For decades, continuous research work is going on to maximize the power harvested from the sun; however, there is only a limited analysis on exploiting the microwatt output power from indoor lightings. Microelectronic system has power demand in the µW range, and therefore, indoor photovoltaics would be appropriate for micro-energy harvesting appliances. “Energy harvesting is defined as the transfer process by which energy source is acquired from the ambient energy, stored in energy storage element and powered to the target systems”. The theory of energy harvesting is: gathering energy from surroundings and offering technological solutions such as solar energy harvesting, wind energy collection and vibration energy harvesting. “The solar cell or photovoltaic cell (PV), is a device that converts light into electric current using the photoelectric effect”. Factors such as light source, temperature, circuit connection, light intensity, angle and height can manipulate the functions of PV cells. Among these, the most noticeable factor is the light intensity that has a major impact on the operations of solar panels.

This paper aims to design an enhanced prediction model on illuminance or irradiance by an optimized artificial neural network (ANN). The input attributes or the features considered here are temperatures, maxim, TSL, VI, short circuit current, open-circuit voltage, maximum power point (MPP) voltage, MPP current and MPP power, respectively. To enhance the performance of the prediction model, the weights of ANN are optimally tuned by a new self-improved brain storm optimization (SI-BSO) model.

The superiority of the implemented work is compared and proved over the conventional models in terms of error analysis and prediction analysis. Accordingly, the presented approach was analysed and its superiority was proved over other conventional schemes such as ANN, ANN-Levenberg–Marquardt (LM), adaptive-network-based fuzzy inference system (ANFIS) and brainstorm optimization (BSO). In addition, analysis was held with respect to error measures such as mean absolute relative error (MARE), mean square root error (MSRE), mean absolute error and mean absolute percentage error. Moreover, prediction analysis was also performed that revealed the betterment of the presented model. More particularly, the proposed ANN + SI-BSO model has attained minimal error for all measures when compared to the existing schemes. More particularly, on considering the MARE, the adopted model for data set 1 was 23.61%, 48.12%, 79.39% and 90.86% better than ANN, ANN-LM, ANFIS and BSO models, respectively. Similarly, on considering data set 2, the MSRE of the implemented model was 99.87%, 70.69%, 99.57% and 94.74% better than ANN, ANN-LM, ANFIS and BSO models, respectively. Thus, the enhancement of the presented ANN + SI-BSO scheme has been validated effectively.

This work has established an improved illuminance/irradiance prediction model using the optimization concept. Here, the attributes, namely, temperature, maxim, TSL, VI, Isc, Voc, Vmpp, Impp and Pmpp were given as input to ANN, in which the weights were chosen optimally. For the optimal selection of weights, a novel ANN + SI-BSO model was established, which was an improved version of the BSO model.

Projection sintering, a system for selectively sintering large areas of polymer powder simultaneously with a high-power projector is introduced. This paper aims to evaluate the suitability of laser sintering (LS) process parameters for projection sintering, as it uses substantially lower intensities, longer exposure times and larger areas than conventional LS.

The tradeoffs in sintering outcomes are evaluated by creating single layer components with varied exposure times and optical intensities. Some of these components were cross-sectioned and evaluated for degree of densification, while the single-layer thickness and the maximum tensile force was measured for the rest.

Shorter exposure times and higher intensities can create thicker and therefore stronger parts than when equal energy is applied over longer exposures. This is different from LS in which energy input (Andrew’s Number) is accepted as a reliable process variable. This difference is likely because significant thermal energy is lost from the sintering region during the exposure time – resulting in reduced peak temperatures. These thermal losses can be offset by imparting additional energy through increased exposure time or light intensity.

Most methods for evaluating LS process parameters, such as the energy melt ratio and Andrew’s Number, estimate energy input from basic process parameters. These methods do not account for thermal losses and assume that the powder absorbs all incident light. These methods become increasingly inaccurate for projection sintering with visible light where exposure times are much higher (>1s) and a larger portion of the light is reflected from the power’s surface. Understanding the appropriate sintering criteria is critical for the development of long-exposure sintering.

A new method of selectively sintering large areas is introduced that could sinter a wider variety of materials by enabling longer sintering times and may increase productivity relative to LS. This work shows that new processing parameters are required for projection sintering as traditional LS process parameters are inadequate.