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All Journal Applied Research and Smart Technology (ARSTech) International Journal of Robotics and Control Systems
Azlan, Norsinnira Zainul
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Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Physics

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Low-cost pick and place anthropomorphic robotic arm for the disabled and humanoid applications Azlan, Norsinnira Zainul; Sanni, Mubeenah Titilola; Shahdad, Ifrah
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 2 (2020): Applied Research and Smart Technology (ARSTech)
Publisher : Department of Mechanical Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i2.25

Abstract

This paper presents the design and development of a new low-cost pick and place anthropomorphic robotic arm for the disabled and humanoid applications. Anthropomorphic robotic arms are weapons similar in scale, appearance, and functionality to humans, and functionality. The developed robotic arm was simple, lightweight, and has four degrees of freedom (DOF) at the hand, shoulder, and elbow joints. The measurement of the link was made close to the length of the human arm. The anthropomorphic robotic arm was actuated by four DC servo motors and controlled using an Arduino UNO microcontroller board. The voice recognition unit drove the command input for the targeted object. The forward and inverse kinematics of the proposed new robotic arm has been analysed and used to program the low cost anthropomorphic robotic arm prototype to reach the desired position in the pick and place operation. This paper’s contribution is in developing the low cost, light, and straightforward weight anthropomorphic arm that can be easily attached to other applications such as a wheelchair and the kinematic study of the specific robot. The low-cost robotic arm’s capability has been tested, and the experimental results show that it can perform basic pick place tasks for the disabled and humanoid applications.
Wearable upper limb motion assist robot for eating activity Kashtwari, Uzair; Azlan, Norsinnira Zainul; Shahdad, Ifrah
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 1 (2020): Applied Research and Smart Technology (ARSTech)
Publisher : Department of Mechanical Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i1.28

Abstract

Many people all around the world are suffering from various types of disabilities and need to depend on others to perform activities of daily living. One of the essential daily living activities is eating. The disabled people should be able to eat their food independently at any time and place, without relying on the caregivers. This paper presents the development of a new wearable upper limb motion assist robot for helping the disabled to eat by themselves. The motion assists robot consists of two degrees of freedom (DOF) movement, focusing on the two most crucial upper limb movements in eating activity, which is the elbow flexion/extension and forearm pronation/supination. A light-weight material was used for the fabrication of the wearable motion assist robot, and Arduino was utilized as the microcontroller. The originality of the study was in terms of the design, operational sequence setting, and kinematic analysis of the wearable upper limb motion assist robot that was explicitly focusing on eating activity. The resulted prototype was portable, compact, light in weight, simple and low cost. The experimental results have proven that the proposed wearable upper limb motion assist robot for eating activity was successful in helping the users to perform the main upper extremity motions in eating. The success rate of the proposed system was 80%, and it took 6 seconds for the system to complete one feeding cycle.
Prototype development of mecanum wheels mobile robot: A review Abd Mutalib, Mohd Azri; Azlan, Norsinnira Zainul
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 2 (2020): Applied Research and Smart Technology (ARSTech)
Publisher : Department of Mechanical Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i2.39

Abstract

This paper provides the review and prototype development of mecanum wheels mobile robot (MWMR). Nowadays, there is a high market demand for a wheeled machine or wheeled robot for various applications. The ability to move in any direction without altering even a single wheel makes this type of wheel useful for driving, especially in a narrowed or confined space. Various styles of implementing MWMR are discussed in this paper. The kinematic derivation and dynamic modelling are also presented. Characteristically, mecanum wheels face traditional mobile application issues like jerking and slippage, which contribute to low positioning accuracy and repeatability. Besides, environmental factors like disturbance and uncertainty also contribute to these issues. To eliminate or at least reduce the effect, the control strategies in previous researches have been reviewed and are presented in this paper. Finally, a low-cost prototype of MWMR was developed as an experimental platform for future study.
Low-cost pick and place anthropomorphic robotic arm for the disabled and humanoid applications Azlan, Norsinnira Zainul; Sanni, Mubeenah Titilola; Shahdad, Ifrah
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 2 (2020): Applied Research and Smart Technology
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i2.25

Abstract

This paper presents the design and development of a new low-cost pick and place anthropomorphic robotic arm for the disabled and humanoid applications. Anthropomorphic robotic arms are weapons similar in scale, appearance, and functionality to humans, and functionality. The developed robotic arm was simple, lightweight, and has four degrees of freedom (DOF) at the hand, shoulder, and elbow joints. The measurement of the link was made close to the length of the human arm. The anthropomorphic robotic arm was actuated by four DC servo motors and controlled using an Arduino UNO microcontroller board. The voice recognition unit drove the command input for the targeted object. The forward and inverse kinematics of the proposed new robotic arm has been analysed and used to program the low cost anthropomorphic robotic arm prototype to reach the desired position in the pick and place operation. This paper’s contribution is in developing the low cost, light, and straightforward weight anthropomorphic arm that can be easily attached to other applications such as a wheelchair and the kinematic study of the specific robot. The low-cost robotic arm’s capability has been tested, and the experimental results show that it can perform basic pick place tasks for the disabled and humanoid applications.
Wearable upper limb motion assist robot for eating activity Kashtwari, Uzair; Azlan, Norsinnira Zainul; Shahdad, Ifrah
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 1 (2020): Applied Research and Smart Technology
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i1.28

Abstract

Many people all around the world are suffering from various types of disabilities and need to depend on others to perform activities of daily living. One of the essential daily living activities is eating. The disabled people should be able to eat their food independently at any time and place, without relying on the caregivers. This paper presents the development of a new wearable upper limb motion assist robot for helping the disabled to eat by themselves. The motion assists robot consists of two degrees of freedom (DOF) movement, focusing on the two most crucial upper limb movements in eating activity, which is the elbow flexion/extension and forearm pronation/supination. A light-weight material was used for the fabrication of the wearable motion assist robot, and Arduino was utilized as the microcontroller. The originality of the study was in terms of the design, operational sequence setting, and kinematic analysis of the wearable upper limb motion assist robot that was explicitly focusing on eating activity. The resulted prototype was portable, compact, light in weight, simple and low cost. The experimental results have proven that the proposed wearable upper limb motion assist robot for eating activity was successful in helping the users to perform the main upper extremity motions in eating. The success rate of the proposed system was 80%, and it took 6 seconds for the system to complete one feeding cycle.
Prototype development of mecanum wheels mobile robot: A review Abd Mutalib, Mohd Azri; Azlan, Norsinnira Zainul
Applied Research and Smart Technology (ARSTech) Vol. 1 No. 2 (2020): Applied Research and Smart Technology
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/arstech.v1i2.39

Abstract

This paper provides the review and prototype development of mecanum wheels mobile robot (MWMR). Nowadays, there is a high market demand for a wheeled machine or wheeled robot for various applications. The ability to move in any direction without altering even a single wheel makes this type of wheel useful for driving, especially in a narrowed or confined space. Various styles of implementing MWMR are discussed in this paper. The kinematic derivation and dynamic modelling are also presented. Characteristically, mecanum wheels face traditional mobile application issues like jerking and slippage, contributing to low positioning accuracy and repeatability. Besides, environmental factors like disturbance and uncertainty also contribute to these issues. The control strategies in previous research have been reviewed and presented in this paper to reduce the effect. Finally, a low-cost prototype of MWMR was developed as an experimental platform for future study.
Self-Motion Control Exoskeleton for Upper Limb Rehabilitation with Perceptron Neuron Motion Capture Osman, Mohamad Afwan; Azlan, Norsinnira Zainul; Suwarno, Iswanto; Samewoi, Abdul Rahman; Kamarudzaman, Nohaslinda
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1030

Abstract

Upper limb rehabilitation robot can facilitate patients to regain their original impaired arm function and reduce therapist’ workload. However, the patient does not have a direct control over his/ her arm movement, which may lead to discomfort or even injury. This paper focuses on the development of a self-motion rehabilitation robot using Perception Neuron motion capture, where the movement of the impaired arm imitates the motion of the healthy limb.  The Axis Neuron software receives the healthy upper limb’s motion data from Perception Neuron. Unity serves as the simulation engine software that provides a 3-dimensional animation. ARDUnity acts as the communication platform between Unity software with Arduino. Arduino code is generated using Wire Editor, which avoids the need of the programming to be written in C++ or C#. Finally, Arduino instructs the exoskeleton motors that are connected to the impaired arm to move, following the healthy joint’s motion. The forward kinematics analysis for the robotic exoskeleton has been carried out to identify its workspace. Hardware experimental tests on the elbow and wrist flexion/ extension have shown the root-mean-square errors (RMSE) between the healthy and impaired arms movement to be 1.5809○ and 12.1955○ respectively. The average time delay between the healthy and impaired elbow movement is 0.1 seconds. For the wrist motion, the time delay is 1 second. The experimental results verified the feasibility and effectiveness of the Perception Neuron in realizing the self-motion control robot for upper limb rehabilitation. The proposed system enables the patients to conduct the rehabilitation therapy in a safer and more comfortable way as they can directly adjust the speed or stop the movement of the affected limb whenever they feel pain or discomfort.
Function Approximation Technique-based Adaptive Force-Tracking Impedance Control for Unknown Environment Azlan, Norsinnira Zainul; Yamaura, Hiroshi; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1029

Abstract

An accurate force-tracking in various applications may not be achieved without a complete knowledge of the environment parameters in the force-tracking impedance control strategy. Adaptive control law is one of the methods that is capable of compensating parameter uncertainties. However, the direct application of this technique is only effective for time-invariant unknown parameters. This paper presents a Function Approximation Technique (FAT)-based adaptive impedance control to overcome uncertainties in the environment stiffness and location with consideration of the approximation error in the FAT representation. The target impedance for the control law have been derived for unknown time-varying environment location and constant or time-varying environment stiffness using Fourier Series. This allows the update law to be derived easily based on Lyapunov stability method. The update law is formulated based on the force error feedback. Simulation results in MATLAB environment have verified the effectiveness of the developed control strategy in exerting the desired amount of force on the environment in x-direction, while precisely follows the required trajectory along y-direction, despite the constant or time-varying uncertainties in the environment stiffness and location. The maximum force error for all unknown environment tested has been found to be less than 0.1 N. The test outcomes for various initial assumption of unknown stiffness between 20000N/m to 120000N/m have shown consistent and excellent force tracking. It is also evident from the simulation results that the proposed controller is effective in tracking time-varying desired force under the limited knowledge of the environment stiffness and location.
Co-Authors Abd Mutalib, Mohd Azri Kamarudzaman, Nohaslinda Kashtwari, Uzair Osman, Mohamad Afwan Samewoi, Abdul Rahman Sanni, Mubeenah Titilola Shahdad, Ifrah Suwarno, Iswanto Yamaura, Hiroshi