scholarly journals Robotic Arm Control Algorithm Based on Stereo Vision Using RoboRealm Vision

2015 ◽  
Vol 15 (2) ◽  
pp. 65-74 ◽  
Author(s):  
R. SZABO ◽  
A. GONTEAN
Keyword(s):  
Stereo Vision ◽  
Control Algorithm ◽  
Robotic Arm ◽  
Robotic Arm Control

LEAP MOTION UNDERWATER ROBOTIC ARM CONTROL

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Lee Jun Wei ◽  
Loi Wei Sen ◽  
Zamani Md. Sani
Keyword(s):  
Control Algorithm ◽  
Inverse Kinematic ◽  
Robotic Arm ◽  
Leap Motion ◽  
Robotic Arms ◽  
Gesture Control ◽  
Pick And Place ◽  
Robotic Arm Control ◽  
Reliability Performance ◽  
And Control

The robotic arm structure and control algorithm are designed for a purpose, to pick and place an object task at underwater which is attached to a ROV (Remotely Operated Underwater Vehicle). It is controlled by an innovated gesture control system, Leap Motion controller. The arm structure of pick and place is controlled by Arduino as microcontroller to control the angles and displacements of the servomotor precisely. The detection of position and orientation of the fingers and hands processed by develop control algorithm in Javascript language and sent to the Arduino. Meanwhile, a detailed 3D drawing is drawn precisely by using SolidWorks for the fabrication. After the platform is completed, kinematic and inverse kinematic equations and calculations are programed into JavaScript language for the control algorithm. Lastly, the hardware and software combined all together. With developed control algorithm, the robotic arm mimics human’s fingers and arm movements which more user friendly interface especially underwater scavenging and salvaging. Since it designed for underwater, the accuracy and precision are crucial for robotic arms, it undergo several experiments and tests for investigate reliability performance of developed robotic arm.   

Control Algorithm for an Industrial Robotic Arm Using Computer Vision

2015 ◽  
Vol 9 (2) ◽  
pp. 182
Author(s):  
Germán Buitrago Salazar ◽  
Olga Lucía Ramos ◽  
Dario Amaya
Keyword(s):  
Computer Vision ◽  
Control Algorithm ◽  
Robotic Arm

Fuzzy model predictive control for 2-DOF robotic arms

2018 ◽  
Vol 38 (5) ◽  
pp. 568-575 ◽  
Author(s):  
Weilin Yang ◽  
Wentao Zhang ◽  
Dezhi Xu ◽  
Wenxu Yan
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Fuzzy Model ◽  
Robotic Arm ◽  
Real Time System ◽  
Content Type ◽  
Loop Control ◽  
Robotic Arms ◽  
Intrinsic Nonlinearity ◽  
Robotic Arm Control

Purpose Robotic arm control is challenging due to the intrinsic nonlinearity. Proportional-integral-derivative (PID) controllers prevail in many robotic arm applications. However, it is usually nontrivial to tune the parameters in a PID controller. This paper aims to propose a model-based control strategy of robotic arms. Design/methodology/approach A Takagi–Sugeno (T-S) fuzzy model, which is capable of approximating nonlinear systems, is used to describe the dynamics of a robotic arm. Model predictive control (MPC) based on the T-S fuzzy model is considered, which optimizes system performance with respect to a user-defined cost function. Findings The control gains are optimized online according to the real-time system state. Furthermore, the proposed method takes into account the input constraints. Simulations demonstrate the effectiveness of the fuzzy MPC approach. It is shown that asymptotic stability is achieved for the closed-loop control system. Originality/value The T-S fuzzy model is discussed in the modeling of robotic arm dynamics. Fuzzy MPC is used for robotic arm control, which can optimize the transient performance with respect to a user-defined criteria.

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