IAES International Journal of Robotics and Automation (IJRA)
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Kinematic modelling of three link robot manipulator and joint torque optimization using genetic algorithm in MATLAB
Get PDFThis research article presents the non-linear dynamic of a three-link robotic manipulator formulated by the Newton-Euler method. The planar manipulator is composed of three links and three revolute joints rotating about the z-axis. The three nonlinear non-homogeneous dynamic equations have been solved graphically with the help of MATLAB by phase variable method. The work represents the graphical solution of the transient response of angular position, and angular velocity of each link member for a predetermined interval of time. With the help of simulated value from MATLAB, torque characteristics have been determined for different torque ratios and optimum torque has been derived using a genetic algorithm to move the manipulator in a proper direction
Low-cost multi-sensing fire-fighting robot with obstacle avoidance mechanism
Get PDFRobots are mostly optimized for tasks that require strength exceeding that of humans or for operations in hazardous environments. The fire-fighting robot developed has multiple sensing capabilities with obstacle avoidance mechanisms and is divided into two units: the robot and the static unit. The robot is equipped with three flame sensors to detect flames (infrared radiation) in three directions, an ultrasonic sensor to avoid obstacles, a wireless receiver to receive data from the static unit, a magnetometer giving the robot a sense of direction, and a unit of Arduino Mega microcontroller serving as the central controlling platform. The static unit has four flame sensors and a transmitter that transmits signals to the robot unit, which an Arduino Uno directly controls. A prototype was developed, which helps prevent the escalation of fires in the home as it can detect, navigate and extinguish flames while avoiding obstacles autonomously
Distributed and autonomous multi-robot for task allocation and collaboration using a greedy algorithm and robot operating system platform
Get PDFResearch investigations in the realm of micro-robotics often center around strategies addressing the multi-robot task allocation (MRTA) problem. Our contribution delves into the collaborative dynamics of micro-robots deployed in targeted hostile environments. Employing advanced algorithms, these robots play a crucial role in enhancing and streamlining operations within sensitive areas. We adopt a tailored GREEDY approach, strategically adjusting weight parameters in a multi-objective function that serves as a cost metric. The objective function, designed for optimization purposes, aggregates the cost functions of all agents involved. Our evaluation meticulously examines the MRTA efficiency for each micro-robot, considering dependencies on factors such as radio connectivity, available energy, and the absolute and relative availability of agents. The central focus is on validating the positive trend associated with an increasing number of agents constituting the cluster. Our methodology introduces a trio of micro-robots, unveiling a flexible strategy aimed at detecting individuals at risk in demanding environments. Each micro-robot within the cluster is equipped with logic that ensures compatibility and cooperation, enabling them to effectively execute assigned missions. The implementation of MRTA-based collaboration algorithms serves as an adaptive strategy, optimizing agents' mobility based on specific criteria related to the characteristics of the target site.
Faults-as-address simulation
Get PDFFault-as-address-simulation (FAAS) is a simulation mechanism for testing combinations of circuit line faults, represented by the bit addresses of element logical vectors. The XOR relationship between the test set T and the truth table L of the element forms a deductive vector for fault simulation, using truth table addresses or the logic vector bits. Addresses are used in the simulation matrix to mark those n-combinations of input faults detected at the element's output. The columns of the simulation matrix are treated as n-row addresses to generate an element output row via a deductive vector. There is no transport of input faults to the element output, Only the 1-signals written in the non-input row coordinates of the circuit simulation matrix. The simulation matrix is initially filled with 1-signals along the main diagonal. The line faults detected on the test set of circuits are determined by the inverse of lines good values, which have 1-values in the matrix row corresponding to the output circuit element. The deductive vector is obtained by the XOR-relations between the test set and logical vector in three table operations. The advantage of the proposed FAAS mechanism is the predictable complexity of the algorithm and memory consumption for storing data structures when simulating a test set
A holistic approach of stability using material parameters of manipulators
Get PDFThe demand for a comprehensive method to assess stability using manipulator material parameters is high. Various material parameters, such as the Young modulus, which represents stiffness, damping, and deflection, influence the material of the robot manipulator. The correlation between robot stability and these characteristics remains unclear, as prior studies have not yet examined the collective impact of these parameters on robot manipulators. This work considers two sophisticated manipulators, namely ABB and FANUC. The main objective of this research is to construct a stability model that considers the material properties of stiffness, damping, and deflection to assess the manipulatorβs stability level, which may be categorized as low, medium, or high. Furthermore, the presented stability model examines and employs numerous modified and conventional formulas for material properties to determine the level of stability. The findings show that stiffness significantly influences the stability of robot manipulators, a relationship that applies to all the examined manipulators. We also emphasize that the choice of manipulator materials significantly impacts stability maintenance. These findings are expected to enhance the design and advancement of novel robot manipulators within the industry
Robot navigation on inclined terrain using social force model
Get PDFThis research introduces an innovative approach to address the limitations of the commonly used social force model-based robot navigation method on flat terrain when applied to sloped terrain. The incline of the terrain becomes a crucial factor in calculating the robotβs steering output when navigating from the initial position to the target position while avoiding obstacles. Therefore, we propose a social forced model-based robot navigation system that can adapt to inclined terrain using inertial measurement unit sensor assistance. The system can detect the surface incline in real time and dynamically adjust friction and gravitational forces, ensuring the robotβs speed and heading direction are maintained. Simulation results conducted using CoppeliaSim show a significant improvement in speed adjustment efficiency. With this new navigation system, the robot can reach its destination in 59.935089 seconds, compared to the conventional social forced model which takes 63.506442 seconds, the robot is also able to reduce slip to reduce wasted movement. This method shows the potential of implementing a faster and more efficient navigation system in the context of inclined terrain
Agricultural path detection systems using Canny-edge detection and Hough transform
Get PDFNavigation is one of the crucial aspects of automation technology within the field of agriculture, such as robotics systems or autonomous agricultural vehicles. Despite many navigation systems having been developed for agricultural land, due to their high development and component costs, these systems are difficult to access for farmers or organizations with limited capital. In this study, the Canny-edge detection and Hough transform methods are implemented in a path detection system on agricultural land to find an alternative, cost-effective navigation system for autonomous farming robots or vehicles. The system is tested on ground-level view images, which are captured from a low perspective and under three different lighting conditions. The testing and experimentation process involves adjusting the parameters of the Canny-edge detection and Hough transform methods for different lighting conditions. Subsequently, an evaluation is conducted using Intersection over Union to obtain the best accuracy results, followed by fine-tuning of the canny-edge detection and Hough transform method parameters. The identified parameters, specifically a 15Γ15 Gaussian kernel, low threshold of 50, high threshold of 150, Hough threshold, minimum line length of 150, and maximum line gap, have been discerned as optimal for the canny-edge and Hough transform algorithms under medium lighting conditions (G=1.0). The observed efficacy of these parameter configurations suggests the methodβs viability for implementation in path detection systems for agricultural vehicles or robots. This underscores its potential to deliver reliable performance and navigate seamlessly across diverse lighting scenarios within the agricultural context
Integrating artificial immune systems and multi-layer perceptron-biogeography-based optimization for enhanced inverse kinematics in robotic arm
Get PDFDetermining required joint angles to achieve a desired position in a manipulatorβs arm is a complicated problem without simple analytical solutions. This paper researches several computational methods based on artificial intelligence (AI) for calculating the joint positions of the 6-DOF robotic arm. We can extrapolate relevance, for example, to the crucial role that robotic manipulator arms play in industrial and medical applications, where enhanced precision and movement efficiency may sharply boost performance and expand applicability. Here, we investigate the effectiveness of methods, such as the artificial immune system (AIS) and multi-layer perceptron-biogeography-based optimization (MLP-BBO). Those AI-driven methods have been applied to determine joint angles for reaching desired positions through simulations for the robotic arm. The results show that the AIS and MLP-BBO approach can handle the intrinsic complexities of the task, thus testifying to the practicability and dependability of these two methods in this application. From the findings in the study, it was indicated that AI-driven techniques can effectively answer the complex problem of the robotic manipulator arm in finding joint angles
Switching regulator based on an adaptive DC-DC buck converter for a lithium-ion battery charging interface
Get PDFA switching regulator based on an adaptive DC-DC buck converter for a Li-ion battery charging interface is introduced in this paper with the aim of improving the efficiency of charging the Li-ion battery during the whole charging process. By using the battery voltage as feedback, an adaptive reference is generated. This reference is employed by the converter, which is in continuous conduction mode (CCM), to produce a wide adaptive output voltage that closely tracks the battery voltage, intended to serve as the power source for the multimode charging interface. The converter was implemented in a 180 nm complementary metal oxide semiconductor (CMOS) process and simulated using the Cadence Virtuoso tool. With an input voltage of 5 V and a switching frequency selected at 500 kHz, the simulation results show that the converter produces different charging currents for each battery charging mode, and an adaptive output voltage ranging from 2.8 V to 4.38 V, with the current ripple of 38 mA in CC mode and voltage ripple factor less than 1% in constant voltage (CV) mode. The average converter efficiency is 83.5%
Aerial robot swarms: a review
Get PDFThe purpose of this review is to highlight the current research on aerial robot swarms and their applications. It focuses on the system architecture and follows the current trend in aerial robotics promoting research in this field along with its impact on society. Further, it explores the dynamics as well as the flying mechanisms of a drone and sheds light on the different algorithms being used to control aerial swarms. Due to a lot of research going on in this field, we also discuss the different trends that are active and of keen interest to the researchers, including the swarm pattern formation behavior