Adaptive Visual Servoing Control of robot Manipulator for Trajectory Tracking tasks in 3D Space

Behzadi-Khormouji, Hamed; Derhami, Vali; Rezaeian, Mehdi

doi:10.1109/icrom.2017.8466231

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…The first five projects [1][2][3][4][5] share almost the same goal: having the robot locate objects in 3D space and then do the relocating or repositioning tasks. In contrast, the second half of the papers [6][7][8][9][10] focus on other goals, purposes, and applications. Additionally, the approach of this project is to have the depth sensor connected to the base of the robotic arm in a way that shows a front field of view for the objects around it (the reason for this approach is explained in the introduction section of this report), this approach found to be followed in papers [1][2].…”

Section: B Related Researchmentioning

confidence: 99%

Developing an Object Detection and Gripping Mechanism Algorithm using Machine Learning

Mohammad,

Kishore,

Prasetyo

2023

J. of App. Sci. & Adv. Eng.

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Localizing and recognition of objects are critical problems for indoor manipulation tasks. This paper describes an algorithm based on computer vision and machine learning that does object detection and gripping tasks. Detection of objects is carried out using a combination of a camera and depth sensor using a Kinect v1 depth sensor. Moreover, machine learning algorithms (YOLO) are used for computer vision. The project presents a method that allows the Kinect sensor to detect objects' 3D location. At the same time, it is attached to any robotic arm base, allowing for a more versatile and compact solution to be used in stationary places using industrial robot arms or mobile robots. The results show an error of locating an object to be 5 mm. and more than 70% confidence in detecting objects correctly. There are many possibilities in which this project can be used, such as in industrial fields, to sort, load, and unload different kinds of objects based on their type, size, and shape. In agriculture fields, to collect or sort different kinds of fruits, in kitchens and cafes where sorting objects like cups, bottles, and cans can occur. Also, this project can be added to mobile robots to do indoor human services or collect trash from different places.

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Section: B Related Researchmentioning

confidence: 99%

Developing an Object Detection and Gripping Mechanism Algorithm using Machine Learning

Mohammad,

Kishore,

Prasetyo

2023

J. of App. Sci. & Adv. Eng.

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“…In [13], an adaptive visual servo controller for trajectory tracking was presented using a calibrated Kinect camera, which acted as a dense stereo sensor, and a controller based only on the inverse kinematic model of the manipulator with a position-based control law. The authors did not provide a stability analysis of the proposed system, and the performance of the controller was verified through experimental results considering only the Root Mean Squared Error (RMSE) of the position of the robot end effector as representative of the controller's precision.…”

Section: Introductionmentioning

confidence: 99%

Adaptive 3D Visual Servoing of a Scara Robot Manipulator with Unknown Dynamic and Vision System Parameters

2021

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In the present work, we develop an adaptive dynamic controller based on monocular vision for the tracking of objects with a three-degrees of freedom (DOF) Scara robot manipulator. The main characteristic of the proposed control scheme is that it considers the robot dynamics, the depth of the moving object, and the mounting of the fixed camera to be unknown. The design of the control algorithm is based on an adaptive kinematic visual servo controller whose objective is the tracking of moving objects even with uncertainties in the parameters of the camera and its mounting. The design also includes a dynamic controller in cascade with the former one whose objective is to compensate the dynamics of the manipulator by generating the final control actions to the robot even with uncertainties in the parameters of its dynamic model. Using Lyapunov’s theory, we analyze the two proposed adaptive controllers for stability properties, and, through simulations, the performance of the complete control scheme is shown.

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Fuzzy Logic Control Design for 2-Link Robot Manipulator in MATLAB/Simulink via Robotics Toolbox

Namazov

2018

2018 Global Smart Industry Conference (GloSIC)

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Adaptive Visual Servoing Control of robot Manipulator for Trajectory Tracking tasks in 3D Space

Cited by 4 publications

References 10 publications

Developing an Object Detection and Gripping Mechanism Algorithm using Machine Learning

Developing an Object Detection and Gripping Mechanism Algorithm using Machine Learning

Adaptive 3D Visual Servoing of a Scara Robot Manipulator with Unknown Dynamic and Vision System Parameters

Fuzzy Logic Control Design for 2-Link Robot Manipulator in MATLAB/Simulink via Robotics Toolbox

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