Design and development of a delta robot system to classify objects using image processing

In this paper, a delta robot is designed to grasp objects in an automatic sorting system. The system consists of a delta robot arm for grasping objects, a belt conveyor for transmitting objects, a camera mounted above the conveyor to capture images of objects, and a computer for processing images to classify objects. The delta robot is driven by three direct current (DC) servo motors. The controller is implemented by an Arduino board and Raspberry Pi 4 computer. The Arduino is programmed to provide rotation to each corresponding motor. The Raspberry Pi 4 computer is used to process images of objects to classify objects according to their color. An image processing algorithm is developed to classify objects by color. The blue, green, red (BGR) image of objects is converted to HSV color space and then different thresholds are applied to recognize the object’s color. The robot grasps objects and put them in the correct position according to information received from Raspberry. Experimental results show that the accuracy when classifying red and yellow objects is 100%, and for green objects is 97.5%. The system takes an average of 1.8 s to sort an object

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

This paper develops a multi-robotic arm system and a stereo vision system to sort objects in the right position according to size and shape attributes. The robotic arm system consists of one master and three slave robots associated with three conveyor belts. Each robotic arm is controlled by a robot controller based on a microcontroller. A master controller is used for the vision system and communicating with slave robotic arms using the Modbus RTU protocol through an RS485 serial interface. The stereo vision system is built to determine the 3D coordinates of the object. Instead of rebuilding the entire disparity map, which is computationally expensive, the centroids of the objects in the two images are calculated to determine the depth value. After that, we can calculate the 3D coordinates of the object by using the formula of the pinhole camera model. Objects are picked up and placed on a conveyor branch according to their shape. The conveyor transports the object to the location of the slave robot. Based on the size attribute that the slave robot receives from the master, the object is picked and placed in the right position. Experiment results reveal the effectiveness of the system. The system can be used in industrial processes to reduce the required time and improve the performance of the production line

Support vector machine-based object classification for robot arm system

In this paper, a support vector machine (SVM) model is trained to classify objects in the automatic sorting system using a robot arm. The robot arm is used to grab objects and move them to the right position according to their shape predicted by the SVM model. The position of objects in the image is identified by using the contouring technique. The centroid of objects is calculated from the image moment of the object's contour. The calibration is conducted to get the parameters of the camera and combine with the pinhole camera model to compute the 3D position of the objects. The feature vector for SVM training is the zone feature and the SVM kernel is the Gaussian kernel. In the experiment, the SVM model is used to classify four objects with different shapes. The results show that the accuracy of the SVM classifier is 99.72%, 99.4%, 99.4% and 99.88% for four objects, respectively

Path Following and Avoiding Obstacle for Mobile Robot Under Dynamic Environments Using Reinforcement Learning

Obstacle avoidance for mobile robot to reach the desired target from a start location is one of the most interesting research topics. However, until now, few works discuss about working of mobile robot in the dynamic and continuously changing environment. So, this issue is still the research challenge for mobile robots. Traditional algorithm for obstacle avoidance in the dynamic, complex environment had many drawbacks. As known that Q-learning, the type of reinforcement learning, has been successfully applied in computer games. However, it is still rarely used in real world applications. This research presents an effectively method for real time dynamic obstacle avoidance based on Q-learning in the real world by using three-wheeled mobile robot. The position of obstacles including many static and dynamic obstacles and the mobile robot are recognized by fixed camera installed above the working space. The input for the robot is the 2D data from the camera. The output is an action for the robot (velocities, linear and angular parameters). Firstly, the simulation is performed for Q-learning algorithm then based on trained data, The Q-table value is implemented to the real mobile robot to perform the task in the real scene. The results are compared with intelligent control method for both static and dynamic obstacles cases. Through implement experiments, the results show that, after training in dynamic environments and testing in a new environment, the mobile robot is able to reach the target position successfully and have better performance comparing with fuzzy controller

Development of a SCARA robot arm for palletizing applications based on computer vision

This paper develops a computer vision system integrated with a SCARA robot arm to pick and place objects. A novel method to calculate the 3D coordinates of the objects from a camera is proposed. This method helps simplify the camera calibration process. It requires no knowledge of camera modeling and mathematical knowledge of coordinate transformations. The least square method will predate the Equation describing the relationship between pixel coordinates and 3D coordinates. An image processing algorithm is presented to detect objects by color or pixel intensity (thresholding method). The pixel coordinates of the objects are then converted to 3D coordinates. The inverse kinematic Equation is applied to find the joint angles of the SCARA robot. A palletizing application is implemented to test the accuracy of the proposed method. The kinematic Equation of the robot arm is presented to convert the 3D position of the objects to the robot joint angles. So, the robot moves exactly to the required positions by providing suitable rotational movements for each robot joint. The experiment results show that the robot can pick and place 27 boxes on the conveyor to the pallet with an average time of 2.8s per box. The positions of the boxes were determined with an average error of 0.5112mm and 0.6838mm in the X and Y directions, respectively

Design a low-cost delta robot arm for pick and place applications based on computer vision

In this paper, we develop a low-cost delta robot arm for grasping objects of unspecified size thanks to a vision system. Stepper motors are used instead of ac servo motors to build a low-cost delta robot arm. Furthermore, we use available materials and machining methods such as laser cutting and 3d printing instead of CNC milling and turning to reduce fabrication costs. The controller is based on a low-cost embedded controller - Arduino Uno for controlling the robot's motion. The vision system is constructed to determine the 3D coordinate of objects in the workspace as well as the sizes of objects. The gripper is opened with a distance of two fingers equal to the size of the objects, and the robot is controlled to the objects' coordinates to grasp them. An application to pick up objects on a conveyor belt is developed to validate the design. The experimental results show that the robot system works correctly, the robot arm moves smoothly, and the information determined by the vision system has a small error, ensuring that the robot can accurately pick up products

A generalised finite difference scheme based on compact integrated radial basis function for flow in heterogeneous soils

In the present paper, we develop a generalised finite difference approach based on compact integrated radial basis function (CIRBF) stencils for solving highly nonlinear Richards equation governing fluid movement in heterogeneous soils. The proposed CIRBF scheme enjoys a high level of accuracy and a fast convergence rate with grid refinement owing to the combination of the integrated RBF approximation and compact approximation where the spatial derivatives are discretised in terms of the information of neighbouring nodes in a stencil. The CIRBF method is first verified through the solution of ordinary differential equations, 2-D Poisson equations and a Taylor-Green vortex. Numerical comparisons show that the CIRBF method outperforms some other methods in the literature. The CIRBF method in conjunction with a rational function transformation method and an adaptive time-stepping scheme is then applied to simulate 1-D and 2-D soil infiltrations effectively. The proposed solutions are more accurate and converge faster than those of the finite different method employed with a second-order central difference scheme. Additionally, the present scheme also takes less time to achieve target accuracy in comparison with the 1D-IRBF and HOC schemes

Characterization of pig farms in Hung Yen, Hai Duong and Bac Ninh provinces

peer reviewedIn order to characterization of pig farms in the Red River Delta, a study was conducted on 90 pig farms in Hung Yen, Hai Duong and Bac Ninh provinces from June to December 2006. Results show that most of the pig farms had been built for five years with a small size (0.5 hectare per farm). The invested capital was about 300-400 millions VND per farm. Four main sow groups used in the farms included crossbred exotic sows (51.1%), crossbred sow between local and exotic breeds (14.4%), purebred Landrace and Yorkshire breeds (15.6 and 18.9%, respectively). The boars were various (Duroc 30%, Yorkshire 21%, Landrace 13%, PiÐtrain × Duroc 36% and others). The pigs farms were faced with several difficulties such as limited land, lack of invested capital, uncontrolled quality of breeding pigs, high costs of feed, poor hygiene condition and diseases

Design of Mobile Manipulator for Fire Extinguisher Testing. Part I Key Specifications and Conceptual Design

All flames are extinguished as early as possible, or fire services have to deal with major conflagrations. This leads to the fact that the quality of fire extinguishers has become a very sensitive and important issue in firefighting. Inspired by the development of automatic fire fighting systems, this paper proposes key specifications based on the standard of fire extinguishers that is ISO 7165:2009 and ISO 11601:2008, and feasible solutions to design a mobile manipulator for automatically evaluating the quality or, more specifically, power of fire extinguishers. In addition, a part of the mechanical design is also discussed.Comment: 10 pages, 8 figures, the 7th International Conference on Advanced Engineering, Theory and Application

ADI method based on C2-continuous two-node integrated-RBF elements for viscous flows

We propose a C2-continuous alternating direction implicit (ADI) method for the solution of the streamfunction-vorticity equations governing steady 2D incompressible viscous fluid flows. Discretisation is simply achieved with Cartesian grids. Local two-node integrated radial basis function elements (IRBFEs) [D.-A. An-Vo, N. Mai-Duy, T. Tran-Cong, A C2-continuous control-volume technique based on Cartesian grids and two-node integrated-RBF elements for second-order elliptic problems, CMES: Computer Modeling in Engineering & Sciences 72 (2011) 299-334] are used for the discretisation of the diffusion terms, and then the convection terms are incorporated into system matrices by treating nodal derivatives as unknowns. ADI procedure is applied for the time integration. Following ADI factorisation, the two-dimensional problem becomes a sequence of one-dimensional problems. The solution strategy consists of multiple use of a one-dimensional sparse matrix algorithm that helps saving the computational cost. High levels of accuracy and efficiency of the present methods are demonstrated with solutions of several benchmark problems defined on rectangular and non-rectangular domains