An Fuzzy Logic Simulation As a Teaching-Learning Media for Artificial Intelligence Class

Dewi, Tresna; Risma, Pola; Oktarina, Yurni

doi:10.14313/jamris_3-2018/13

Cited by 7 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Each of these AIs can be implemented individually or in combination to have a better impact. However, the robot implementation group's issue is simplicity; therefore, the most used AI is proposed in this study, i.e., Fuzzy Controller Logic [30,31,32].…”

Section: Introductionmentioning

confidence: 99%

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

Dewi

Anggraini

Risma

et al. 2021

Sinergi

Self Cite

View full text Add to dashboard Cite

As robots' use increases in every sector of human life, the demand for cheap and efficient robots has also enlarged. The use of two or more simple robot is preferable to the use of one sophisticated robot. The agriculture industry can benefit from installing a robot, from seeding to the packaging of the product. A precise analysis is required for the installation of two collaborative robots. This paper discusses the motion control analysis of two collaborative arms robots in the fruit packaging system. The study begins with the relative motion analysis between two robots, starting with kinematics modeling, image processing for object detection, and the Fuzzy Logic Controller's design to show the relationship between the robot inputs and outputs. The analysis is carried out using SCILAB, open-source software for numerical computing engineering. This paper is intended as the initial analysis of the feasibility of the real experimental system.

show abstract

Section: Introductionmentioning

confidence: 99%

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

Dewi

Anggraini

Risma

et al. 2021

Sinergi

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, in order to achieve gripper's smooth motion, artificial intelligence (AI) is applied to utilize the input from the attached sensors at a robot's system. The commonly used AI is the fuzzy logic controller (FLC) [22][23][24][25] and the neural network (NN) [26][27][28]. Many kinds of research have applied inverse kinematics to generate a robot trajectory.…”

Section: Introductiomentioning

confidence: 99%

Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller

Dewi

Nurmaini

Risma

et al. 2020

IJECE

Self Cite

View full text Add to dashboard Cite

The arm robot manipulator is suitable for substituting humans working in tomato plantation to ensure tomatoes are handled efficiently. The best design for this robot is four links with robust flexibility in x, y, and z-coordinates axis. Inverse kinematics and fuzzy logic controller (FLC) application are for precise and smooth motion. Inverse kinematics designs the most efficient position and motion of the arm robot by adjusting mechanical parameters. The FLC utilizes data input from the sensors to set the right position and motion of the end-effector. The predicted parameters are compared with experimental results to show the effectiveness of the proposed design and method. The position errors (in x, y, and z-axis) are 0.1%, 0.1%, and 0.04%. The rotation errors of each robot links (θ1, θ2, and θ3) are 0%, 0.7% and 0.3%. The FLC provides the suitable angle of the servo motor (θ4) responsible in gripper motion, and the experimental results correspond to FLC’s rules-based as the input to the gripper motion system. This setup is essential to avoid excessive force or miss-placed position that can damage tomatoes. The arm robot manipulator discussed in this study is a pick and place robot to move the harvested tomatoes to a packing system.

show abstract

“…Proportional-integral-differential (PID) controller is the primary controller used in most robots applications, and however, in most cases, the PID controller only is not enough for controlling the robot [11] [12]. An artificial intelligence (AI) needs to be added, one of the AI is the fuzzy logic controller (FLC) [13] [14]. Robotics is entitled with complex mathematical modeling.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator

et al. 2019

View full text Add to dashboard Cite

Arm robot manipulator is the most applied robot to substitute human labor in industries. Due to the importance of arm robot manipulator in manufacturing lines, the robustness and effective design are essential in building an arm robot. This paper presents the controller, mechanical, and motion designs of an arm robot manipulator. The fuzzy logic controller is employed to ensure the effectiveness in detecting the target object. PID controller is designed to enhance the smooth and stability of robot motion. The simulation of how the robot move inside its workspace was conducted using RSTX toolbox in SciLab. The motion is generated by deriving Denavit-Hartenberg parameters of the mechanical design. The result shows the effective design of Fuzzy-PID controller and mechanical design of a pick and places arm robot manipulator.

show abstract

An Fuzzy Logic Simulation As a Teaching-Learning Media for Artificial Intelligence Class

Cited by 7 publications

References 24 publications

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

Motion Control Analysis of Two Collaborative Arm Robots in Fruit Packaging System

Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller

Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator

Contact Info

Product

Resources

About