IAES International Journal of Robotics and Automation (IJRA)
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Vector-logic computing for faults-as-address deductive simulation
Get PDFThe aim of the research is to create logic-free vector computing, leveraging read-write transactions in memory, to solve the problems of modeling and simulation stuck-at-fault combinations for complex logic elements and digital structures. At the same time, the problem of creating smart data structures based on logical vectors, truth tables, and deductive matrices is considered to simplify algorithms for parallel stuck-at-fault simulation. Vector computing is a computational process based on read-write transactions on bits of a binary vector of functionality, where the input data and faults are the addresses of the bits. A method for the synthesis of deductive vectors for propagating input fault lists is proposed, which has a quadratic computational complexity of read-write transactions. Deductive vectors, combined into a quadratic matrix, represent explicit data structures for parallel simulation of single and multiple stuck-at-faults. The initial information for constructing a deductive matrix is a logical vector and a bit-recoding matrix. Matrix is easily obtained using a recursive procedure based on the combinatorial properties of the truth table. Considering emerging trends, focused on in-memory computing, an algorithm for fault, as addresses, simulation is proposed, using logical and deductive vectors placed in memory. The simulation algorithm is proposed not to use commands of powerful processors
The use of artificial intelligence in interrogation: lies and truth
Get PDFFollowing the development of artificial intelligence technology, a new trend has emerged in which this technology is increasingly used in case investigations. In this study, we developed a lie detection system that can instantly determine whether an interrogee is lying depending on their emotional responses to specific questions. Investigators then use these data, in addition to their personal experiences and case information, to adjust their interrogation strategies and techniques, thereby leading the interrogee to confess and accelerating the investigation process. Our system collects data using OpenFace and performs deep learning using gcForest. Deep learning training was performed using a real-life trial dataset, the Miami University Deception Detection Database, and a bag-of-lies dataset, and their corresponding trained systems achieved a detection accuracy of 95.11%, 90.83%, and 88.19%, respectively
Assembling, simulating, and recording robot videos as an effort to motivate middle school students and teachers of Science in Bengkulu Province
Get PDFThe aim of this study was to determine the motivation of science teachers and students towards science after participating in the activity of assembling, simulating, and recording line follower robots as an effort to motivate middle school students and teachers towards science in Bengkulu Province. The research was done by direct practicing, where 60 students and 15 teachers of three junior high school (SMP): SMP Negeri 06 Seluma, SMP Negeri 02 Kota Bengkulu, and SMP Negeri 8 Rejang Lebong, were involved as the research subjects. The research activity concluded that the schools are ready to prepare simple electronics/robot laboratories for the three research subjects and the science teachers and students were motivated to learn science. It was seen from the score of 3.95 (scale of 1 to 5) for students, and for the science teacher, the score was 3.83 (scale of 1 to 5). The science teachers will follow up on robotics activities so that students will be interested in learning science at home and school
Designing and implementing a multi-function board to increase the operation time of mobile robots using solar panels
Get PDFToday, the use of mobile robots and autonomous vehicles has increased due to their use in various industries, and their performance and duration of operation largely depend on the amount of energy consumed and their batteries. One of the ways to increase the operation time of robots is the use of solar panels that can charge their batteries while moving, but the amount of energy received from solar panels reduces their efficiency due to factors affecting them, such as the angle of the sun, weather conditions, and their use in mobile robots alone is not recommended. In this research, we introduce an electric circuit with very low losses to increase the received power of solar panels and increase their efficiency, which is able to supply the power of the robot through solar panels when the sunlight and the angle of radiation are suitable and charge the batteries through the maximum power point controller (MPPC), and by reducing the amount of energy received from the panels by changing the energy source to the battery, the duration of the system’s dependence on the battery has decreased, which increases the duration of the mobile robots
Conceptual design and simulation study of an autonomous indoor medical waste collection robot
Get PDFSolid waste management is one of the critical challenges seen everywhere, and the coronavirus disease (COVID-19) pandemic has only worsened the problems in the safe disposal of infectious waste. This paper outlines a design for a mobile robot that will intelligently identify, grasp, and collect a group of medical waste items using a six-degree of freedom (DoF) arm, You Only Look Once (YOLO) neural network, and a grasping algorithm. Various designs are generated before running simulations on the selected virtual model using Robot Operating System (ROS) and Gazebo simulator. A lidar sensor is also used to map the robot's surroundings and navigate autonomously. The robot has good scope for waste collection in medical facilities, where it can help create a safer environment
DEMAP: differential evolution mapping for network on chip optimization
Get PDFNetwork-on-chip (NoC) is a new paradigm for system-on-chip (SoC) design, which facilitates the interconnection and integration of complex components. Since this technology is still new, significant research efforts are needed to accelerate and simplify the design phases. Mapping is a critical phase in the NoC design process, as a mismatch of application software components can significantly impact the final system's performance. Therefore, it is essential to develop automated tools and methods to ensure this step. The main objective of this project is to develop a new approach that can be used to map applications on the NoC architecture to reduce communication costs. To achieve this goal, we have opted for an optimization algorithm, specifically the differential evolution algorithm
Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm
Get PDFNowadays, most robotic systems perform their tasks in an environment that is generally known. Thus, robot’s trajectory can be planned in advance depending on a given task. However, as a part of modern manufacturing systems which are faced with the requirements to produce high product variety, mobile robots should be flexible to adapt to changing and diverse environments and needs. In such scenarios, a modification of the task or a change in the environment, forces the operator to modify robot’s trajectory. Such modification is usually expensive and time-consuming, as experienced engineers must be involved to program robot’s movements. The current paper presents a solution to this problem by simplifying the process of teaching the robot a new trajectory. The proposed method generates a trajectory based on an initial raw demonstration of its shape. The new trajectory is generated in such a way that the errors between the actual and target end positions and orientations of the robot are minimized. To minimize those errors, the grey wolf optimization (GWO) algorithm is applied. The proposed approach is demonstrated for a two-wheeled mobile robot. Simulation and experimental results confirm high accuracy of generated trajectories
Development and integration of laser sensor tracking system in robotic arm for path correction during welding operation
Get PDFAn industrial robot is mainly used for manufacturing. Industrial robots are 6 or more axes, which can be automatically controlled by programming. Typical applications of robots include welding, painting, picking, and placing printed circuit boards, packaging and labelling, palletizing, product inspection, and testing with high accuracy, precision, and fast speed. Robotic welding is a complex, nonlinear and time varying process which can be affected by various natural or any random disturbances. Due to the effect of various factors, the actual welding path may differ. So, welding robots should be able to detect the actual welding path, then adjust the difference in welding path and complete the welding process accurately. Laser welding is one of the most important technologies in the manufacturing field. It is the most frequently used technology which has made new demands. So, the manufacturer ensures to meet the quality of laser welding and improve the production efficiency. Due to the increase in demand of quality, accuracy, precise, productivity, flexibility and adaptive control of welding robot, an automatic laser seam tracking system is developed with welding robot to precisely follow the welding path and make the necessary corrections during welding operations
Implementation of a complex fractional order proportional-integral-derivative controller for a first order plus dead time system
Get PDFThis paper presents the implementation of a complex fractional order proportional integral derivative (CPID) and a real fractional order PID (RPID) controllers. The analysis and design of both controllers were carried out in a previous work done by the author, where the design specifications were classified into easy (case 1) and hard (case 2) design specifications. The main contribution of this paper is combining CRONE approximation and linear phase CRONE approximation to implement the CPID controller. The designed controllers-RPID and CPID-are implemented to control flowing water with low pressure circuit, which is a first order plus dead time system. Simulation results demonstrate that while the implemented RPID controller fails to stabilize the system in case 2, the implemented CPID controller stabilizes the system in both cases and achieves better transient response specifications
Using mobile laser scanner and imagery for urban management applications
Get PDFDespite autonomous navigation is one of the most proliferate applications of three-dimensional (3D) point clouds and imagery both techniques can potentially have many other applications. This work explores urban digitization tools applied to 3D geometry to perform urban tasks. We focus exclusively on compiling scientific research that merges mobile laser scanning (MLS) and imagery from vision systems. The major contribution of this review is to show the evolution of MLS combined with imagery in urban applications. We review systems used by public and private organizations to handle urban tasks such as historic preservation, roadside assistance, road infrastructure inventory, and public space study. The work pinpoints the potential and accuracy of data acquisition systems to handled both 3D point clouds and imagery data. We highlight potential future work regarding the detection of urban environment elements and to solve urban problems. This article concludes by discussing the major constraints and struggles of current systems that use MLS combined with imagery to perform urban tasks and to solve urban tasks