IAES International Journal of Robotics and Automation (IJRA)
Robots are becoming part of people's everyday social lives and will increasingly become so. In future years, robots may become caretaker assistants for the elderly, or academic tutors for our children, or medical assistants, day care assistants, or psychological counselors. Robots may become our co-workers in factories and offices, or maids in our homes. The IAES International Journal of Robotics and Automation (IJRA) is providing a platform to researchers, scientists, engineers and practitioners throughout the world to publish the latest achievement, future challenges and exciting applications of intelligent and autonomous robots. IJRA is aiming to push the frontier of robotics into a new dimension, in which motion and intelligence play equally important roles. Its scope includes (but not limited) to the following: automation control, automation engineering, autonomous robots, biotechnology and robotics, emergence of the thinking machine, forward kinematics, household robots and automation, inverse kinematics, Jacobian and singularities, methods for teaching robots, nanotechnology and robotics (nanobots), orientation matrices, robot controller, robot structure and workspace, robotic and automation software development, robotic exploration, robotic surgery, robotic surgical procedures, robotic welding, robotics applications, robotics programming, robotics technologies, robots society and ethics, software and hardware designing for robots, spatial transformations, trajectory generation, unmanned (robotic) vehicles, etc.
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Modeling and Control of 5DOF Robot Arm Using Fuzzy Logic Supervisory Control
Mohammad Amin Rashidifar;
Ali Amin Rashidifar;
Darvish Ahmadi
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijra.v2i2.pp56-68
Modeling and control of 5 degree of freedom (DOF) robot arm is the subject of this article. The modeling problem is necessary before applying control techniques to guarantee the execution of any task according to a desired input with minimum error. Deriving both forward and inverse kinematics is an important step in robot modeling based on the Denavit Hartenberg (DH) representation. Proportional integral derivative (PID) controller is used as a reference benchmark to compare its results with fuzzy logic controller (FLC) and fuzzy supervisory controller (FSC) results. FLC is applied as a second controller because of the nonlinearity in the robot manipulators. We compare the result of the PID controller and FLC results in terms of time response specifications. FSC is a hybrid between the previous two controllers. The FSC is used for tuning PID gains since PID alone performs not satisfactory in nonlinear systems. Hence, comparison of tuning of PID parameters is utilized using classical method and FSC method. Based on simulation results, FLC gives better results than classical PID controller in terms of time response and FSC is better than classical methods such as Ziegler-Nichols (ZN) in tuning PID parameters in terms of time response.
Depth Level Control System using Peripheral Interface Controller for Underwater Vehicle
Muhamad Fadli Ghani;
Shahrum Shah Abdullah
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijra.v2i2.pp69-72
This research explained on a design and development of an Automatic Depth Control System for underwater vehicle. Definition of underwater vehicle is a robotic sub-sea that is a part of the emerging field of autonomous and unmanned vehicles. This project shows the implementation’s development of an Automatic Depth Control System on a test prototyping vehicle especially involved small-scale and low cost sub-sea robots. The Automatic Depth Control System assembled with mechanical system and module of electronic system for development of a controller.
UAV Controller Based on Adaptive Neuro-Fuzzy Inference System and PID
Ali Moltajaei Farid
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijra.v2i2.pp73-82
ANFIS is combining a neural network with a fuzzy system results in a hybrid neuro-fuzzy system, capable of reasoning and learning in an uncertain and imprecise environment. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) is employed to control an unmanned aircraft vehicle (UAV). First, autopilots structure is defined, and then ANFIS controller is applied, to control UAVs lateral position. The results of ANFIS and PID lateral controllers are compared, where it shows the two controllers have similar results. ANFIS controller is capable to adaptation in nonlinear conditions, while PID has to be tuned to preserves proper control in some conditions. The simulation results generated by Matlab using Aerosim Aeronautical Simulation Block Set, which provides a complete set of tools for development of six degree-of-freedom. Nonlinear Aerosonde unmanned aerial vehicle model with ANFIS controller is simulated to verify the capability of the system. Moreover, the results are validated by FlightGear flight simulator.
Investigation In Two Wheels Mobile Robot Movement: Stability and Motion Paths
Abdulrahman A.A. Emhemed
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijra.v2i2.pp45-49
This paper deals with the problem of dynamic modelling of inspection robot two wheels. Fuzzy controller based on robotics techniques for optimize of an inspection stability. The target is to enhancement of robot direction and avoids the obstacles. To find collision free area, distance-sensors such as ultra-sonic sensors and laser scanners or vision systems are usually employed. The distance-sensors offer only distance information between mobile robots and obstacles. Also the target are shown can be reached by different directions. The fuzzy logic controller is effect to avoid the abstacles and get ideal direction to “the target box”.
Parallel Graph Transformation based on Merged Approach
Asmaa Aouat;
El Abbassia Deba
IAES International Journal of Robotics and Automation (IJRA) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijra.v2i2.pp50-55
Graph transformation is one of the key concepts in graph grammar. In order to accelerate the graph transformation, the concept of parallel graph transformation has been proposed by different tools such as AGG tool. The theory of parallel graph transformation used by AGG just allows clarifying the concepts of conflict and dependency between the transformation rules. This work proposes an approach of parallel graph transformations which enables dependent transformation rules to be executed in parallel.