Development of the programming and simulation system of 4-axis robot with hybrid kinematic

In the context of the industrialization era, robots are gradually replacing workers in some production stages. There is an irreversible trend toward incorporating image processing techniques in the realm of robot control. In recent years, vision-based techniques have achieved significant milestones. However, most of these techniques require complex setups, specialized cameras, and skilled operators for burden computation. This paper presents an efficient vision-based solution for object detection and grasping in indoor environments. The framework of the system, encompassing geometrical constraints, robot control theories, and the hardware platform, is described. The proposed method, covering calibration to visual estimation, is detailed for handling the detection and grasping task. Our approach's efficiency, feasibility, and applicability are evident from the results of both theoretical simulations and experiments.

Section: Previous Workmentioning

confidence: 99%

Using an HSV-based approach for detecting and grasping an object by the industrial manipulator system

Ngo

2023

“…Stress analysis of robot arm components and optimization structure is performed before manufacturing [14][15][16][17].Analyzing the robot's dynamics and kinematics is also necessary for optimizing robot performance [18][19].The forward kinematics problem is used to calculate the position and orientation of the robot end-effector from the values of joint angles. The Denavit-Hartenberg (DH) parameters are employed to establish the transform matrix between coordinate frames of robot joints.The solution of the inverse kinematics problem is the values of the robot joint angles corresponding to a certain pose of the robot end-effector [20][21][22]. Trajectory planning is the basis of robot motion control and involves the stability of robot motion, working efficiency, energy consumption, etc.…”

Section: Introductionmentioning

confidence: 99%

Design and development of a cost efficiency robot arm with a PLC-based robot controller

Duy

2024

To develop a cost-efficient robot arm for a typical pick and place application that can applied in industry, this paper deployed a programmable logic controller (PLC) to control the rotation motion of the robot joints. The main tasks of the PLC controller are to calculate the kinematics, create high-speed pulse outputs for stepper motors, and implement sequence operations for a certain application. Functions are written into subprogram segments. When needed, the main program only turns on the corresponding flag for executing the subprogram. Using the pre-written subprograms, a logical sequence to implement the Pick and Place application is easily implemented and described in this paper. The PLC program is developed to control a SCARA robot with three rotation joins. Stepper motors drive the robot joints. The Delta DVPSV2 PLC is utilized to design the robot controller. This PLC series has four high-speed pulse output pins, which is suitable for this project. Synchronous motion of stepper motors is easily performed using high-speed pulse output commands built into the PLC program. Experimental results of robot arm control have demonstrated the efficiency and accuracy of the developed program. The robot arm's forward and inverse kinematics problems are verified using the simulator on the software. The robot's joints move synchronously as required to perform pick-and-place applications.

“…A computer processes the vision data to provide useful information to the robot controller. As a result, the robot will complete the requests more accurately and efficiently [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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

Ho,

Vo,

Trung

2023

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.