In this paper, a new algorithm called table-based matching for multi-robot (node) that used for localization and orientation are suggested. The environment is provided with two distance sensors fixed on two beacons at the bottom corners of the frame. These beacons have the ability to scan the environment and estimate the location and orientation of the visible nodes and save the result in matrices which are used later to construct a visible node table. This table is used for matching with visible-robot table which is constructed from the result of each robot scanning to its neighbors with a distance sensor that rotates at 360⁰; at this point, the location and identity of all visible nodes are known. The localization and orientation of invisible robots rely on the matching of other tables obtained from the information of visible robots. Several simulations implementation are experienced on a different number of nodes to submit the performance of this introduced algorithm.
A new algorithm for multi-object recognition and localization is introduced in this paper. This algorithm deals with objects which have different reflectivity factors and distinguish color with respect to the other objects. Two beacons scan multi-color objects using long distance IR sensors to estimate their absolute locations. These two beacon nodes are placed at two corners of the environment. The recognition of these objects is estimated by matching the locations of each object with respect to the two beacons. A look-up table contains the distances information about different color objects is used to convert the reading of the long distance IR sensor from voltage to distance units. The locations of invisible objects are computed by using absolute locations of invisible objects method. The performance of introduced algorithm is tested with several experimental scenarios that implemented on color objects.
Cybersecurity awareness has a huge impact on individuals and an even bigger impact on firms, universities, and institutes to those individuals belong. Consequently, it is essential to explore and asses the factors affecting the awareness level of cybersecurity. More specifically this research study examines the impact of demographic features of individuals on cybersecurity awareness. The Studied literature’s limitations have been addressed and overcome in our research from the variability, and ambiguity aspects. A questionnaire was developed and responses were collected from 613 participants. Reliability and validity tests as well as correlations have been applied for the instruments and data employed in this study. Coefficients were calculated via multiple linear regression for the weights of each of the cybersecurity components. Data reliability test showed that Cronbach’s Alpha value of 0.707 for the used data which is acceptable for research purposes. Results analysis showed r-value for each of the questions is greater than the r table which was 0.07992. Examining the proposed hypotheses showed that there is a difference as the null hypothesis is rejected for one of the demographic features being tested namely, gender. While there is no significant difference when it comes to the other two factors, education level, and age. Using the weight for each of the components, password security, technical behavior, and social influence could provide a solid base for decision-makers to focus on and implement the available resources for gender-specific developments to raise the cybersecurity awareness level..
A robot is a smart machine that can help people in their daily lives and keep everyone safe. the three general sequences to accomplish any robot task is mapping the environment, the localization, and the navigation (path planning with obstacle avoidance). Since the goal of the robot is to reach its target without colliding, the most important and challenging task of the mobile robot is the navigation. In this paper, the robot navigation problem is solved by proposed two algorithms using low-cost IR receiver sensors arranged as an array, and a robot has been equipped with one IR transmitter. Firstly, the shortest orientation algorithm is proposed, the robot direction is corrected at each step of movement depending on the angle calculation. secondly, an Active orientation algorithm is presented to solve the weakness in the preceding algorithm. A chain of the active sensors in the environment within the sensing range of the virtual path is activated to be scan through the robot movement. In each algorithm, the initial position of the robot is detected using the modified binary search algorithm, various stages are used to avoid obstacles through suitable equations focusing on finding the shortest and the safer path of the robot. Simulation results with multi-resolution environment explained the efficiency of the algorithms, they are compatible with the designed environment, it provides safe movements (without hitting obstacles) and a good system control performance. A Comparison table is also provided.
Linearization sensors characteristics becomes very interest field for researchers due to the importance in enhance the system performance, measurement accuracy, system design simplicity (hardware and software), reduce system cost, ..etc. in this paper, two approaches has been introduced in order to linearize the sensor characteristics; first is signal condition circuit based on lock up table (LUT) which this method performed for linearize NTC sensor characteristic. Second is ratiometric measurement equation which this method performed for linearize LVDT sensor characteristic. The proposed methods has been simulated by MATLAB, and then implemented by using Anadigm AN221E04 Field Programmable Analog Array (FPAA) development kit which several experiments performed in order to improve the performance of these approaches.
In this paper, explicit model predictive controller is applied to an inverted pendulum apparatus. Explicit solutions to constrained linear model predictive controller can be computed by solving multi-parametric quadratic programs. The solution is a piecewise affine function, which can be evaluated at each sample to obtain the optimal control law. The on-line computation effort is restricted to a table-lookup. This admits implementation on low cost hardware at high sampling frequencies in real-time systems with high reliability and low software complexity. This is useful for systems with limited power and CPU resources.