•New geometric vector modelling of SCARA robot.•Definition of independent geometric parameters based on robot joints invariants.•A direct parameters identification method based on “Circle Point ...Analysis”.•Improvement of the accuracy of a SCARA robot (mean transformation error less than 0.03 mm).•Improvement of the final accuracy of a SCARA robot compared to first and second-order Denavit–Hartenberg geometrical model.
This article introduces a new geometric vector modeling method of serial kinematic robot consistent with the identification process. This method is based on the definition of position and orientation of the robot joint invariants. For example, the invariant of the rotational joint is a straight-line (rotational joint axis). Thus, only independent geometrical parameters are introduced to model the joint axis position and orientation in space. Note that, the orientation is not constrained as in the Denavit–Hartenberg (DH) formalism. This article presents the methodology to define these geometrical parameters and the geometrical model. In this context, the identification method relies on "Circle Point Analysis". The points are measured with a laser tracker. Indeed, with a relevant processing of the measured points, we directly identify the invariants of joints. This method is applied to a SCARA robot geometric modeling. After an identification process, this methodology allows improving inverse kinematic error compared to the classical DH geometrical model with first and second-order defects. Moreover, the obtained residual error mean value is close to the accuracy of the measurement process.
In this paper, hand tracking based on computer vision is developed to control the movement of a SCARA robot arm. The robot arm will move according to the movement of the human hand. Instead of using ...buttons on the teach-pendant or a computer control program to move the robot arm, the robot can now be easily controlled and positioned quickly by the movement of the operator's hand. A SCARA robot arm with two rotation joints and one translation motion is constructed for the validation system. Two states of the hand are recognized for controlling the vacuum cup to grasp the products. Stepper motors drive the robot arm. Arduino Uno is used as the main controller for controlling the stepper motors. The handtracking is performed by using the MediaPipe Hands framework developed by Google. The coordinates of 21 hand landmarks are extracted for further processing. A program is written on a personal computer to process the image to get the position and state of the hand. This position is transformed into the rotation angles of the robot's joints. Then, the angles and state are sent to the Arduino board. The Arduino board creates pulse signals to rotate the stepper motors. The experimental results show that the robot's trajectory is close to the hand trajectory at a low speed.
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.
The cost of Computer Numerical Control Machines is very high which leads to their widely inaccessible nature by small to mid-range manufacturing companies. Though, the technology is aimed at ...increasing efficiency and accuracy by achieving optimization in the traditional manufacturing methods, its most major drawback is the high cost of maintenance and installation. The article discusses an affordable solution to this issue. As a viable alternative, a SCARA Robotic arm is used to execute the process. The initial computer aided design is analysed for feasibility in real conditions using rigorous finite element methods and experimental validation. The workspace of the SCARA is modelled on general usage approximations; a detailed kinematic and dynamic robotic analysis is also done to ensure better process conditions and the future possibility to achieve force feedback control. This prototype can be operated using user-based systems and can be designed following the methodology proposed in this article. A combination of metals and non-metals are used depending upon various factors such as strength requirements, design complexity and cost. Both traditional and additive manufacturing techniques are employed to manufacture the parts, An Arduino microcontroller is used to execute all control structures and operations. The control for a batch operation can be entered through the touchscreen attached in the robot, with a special mode for individual production. The technology proposed in this paper is aimed at assisting Micro to small manufacturing enterprises (MSMEs) to achieve higher productivity.
The industry robot generally refers the robot, which is used in the mechanical manufacturing industry, replacing the human to complete the mass and high request work. This thesis is based on the ...structure of 4-DOF SCARA robot arm and investigates the problem of the analysis and optimization of the structure of robot arm according to the requirement of system for the rapid response and smooth work.
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.
This article addresses selective compliance assembly robot arm (SCARA) robot path planning using markers. Path planning requires the positions and orientations of goal points. A path planning method ...using markers finds the position and orientation of the markers and recognises the markers one by one to get to the goal points. This method uses two image processes: which are Speeded-Up Robust Features (SURF) and labelling. To obtain the 3D positions of the markers, the coordinate space is transformed from colour space to camera space using a Kinect sensor. This process was implemented on a SCARA robot system. By using D-H (Denavit-Hartenberg) parameters, the SCARA robot's inverse kinematics transforms the extracted points into joint actuator trajectories. After finding the position and orientation of the markers, the path planning is performed. The time-efficiency of the proposed method is validated through experimental results.
To further extend the application of an industrial robot to e.g. the machining, it is crucial to ensure its three-dimensional (3D) positioning accuracy over its entire workspace. Numerous past works ...presented numerical compensation based on the robot kinematic model containing position and orientation errors of rotary axes average lines, widely known as Denavit-Hartenberg (D-H) parameters. This paper presents two novel contributions. First, this paper proposes a kinematic model with the angular positioning deviation “error map” of each rotary axis, which is given as a function of command angular positions. Furthermore, to model the backlash influence, it is modelled dependent also on the direction of rotation. The second contribution is on the proposal of the “open-loop” tracking interferometer measurement to indirectly identify the angular positioning deviation of each rotary axis. It measures the distance from the retroreflector, fixed on the table, to the robot's end effector at many points over the entire workspace by using a laser interferometer attached to the robot's end effector. The identified kinematic model's accuracy is experimentally investigated, and is compared to the conventional D-H model.
•A model to predict an industrial robot's positioning error over its entire workspace is presented.•The proposed model contains the angular positioning deviation “error map” of rotary axes.•The “open-loop” tracking interferometer measurement identifies the angular positioning deviation.•The identified kinematic model's accuracy is experimentally investigated.
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