Robotic Arm Control using Internet of Things (IoT)

Hisham, Amirah â€ ̃Aisha Badrul; Low, Zi Han; Ishak, Mohamad Hafis Izran; Idris, Nurul Hawani

doi:10.11113/elektrika.v18n3-2.201

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…In [8], a controller for a robotic arm created using Internet of Things (IoT) technologies is considered. Such a robotic hand can be controlled via the Internet.…”

Section: Methodsmentioning

confidence: 99%

Research of microprocessor device and software for remote control of a robotic system

Zuiev,

Krylova,

Hapon

et al. 2024

TAPR

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The modern stage of the development of intelligent robotic systems is characterized by the expansion of fields of application, which is due to autonomous work and decision-making in conditions of uncertainty. The object of research is the system of remote control of robotic systems. During the remote control of robotic systems, problems arise that are associated with the use of wireless communication in real time. The article analyzes software and hardware implementations of various remote control systems suitable for use as part of autonomous robotic systems and analyzes promising microcontroller platforms for implementing a remote control device for a robotic system. A brief review of existing protocols for transmitting control signals using radio communication equipment and microprocessor platforms for the development of embedded systems is performed, among which a solution is selected for research. Several approaches to the control of a robotic system are highlighted – control using a wired connection and corresponding protocols, control via wireless communication or via the Internet, control via general-purpose network protocols. The target platform is chosen and justified, and the S.BUS protocol is analyzed with the provision of an algorithm for obtaining the values of the control channels from the S.BUS package. The structure and algorithm of functioning of the microprocessor remote control system based on the ESP32 microcontroller and the FreeRTOS OS are given. A study of the operation process of the proposed remote control system is carried out, for which it is placed on the chassis of a ground autonomous robotic system with four-wheel drive, and the delay time of the control signal from the receiver to the engine control modules is determined. According to the conducted analysis, the expediency of using specialized radio communication equipment with the S.BUS protocol for controlling executive devices as part of a robotic system, for precise movement control in real time, is shown.

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“…In [8], a controller for a robotic arm created using Internet of Things (IoT) technologies is considered. Such a robotic hand can be controlled via the Internet.…”

Section: Methodsmentioning

confidence: 99%

Research of microprocessor device and software for remote control of a robotic system

Zuiev,

Krylova,

Hapon

et al. 2024

TAPR

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“…Robotic arms, controlled by Raspberry Pi 3 Model B + boards, are used in some healthcare settings for wound assessment (Ishak et al, 2018). The robotic arm has three degrees of motion and a grip movement facilitated by four servo motors.…”

Section: Robotic Arm In Wound Assessmentmentioning

confidence: 99%

Robotic Arm Trajectory Based on Machine Learning for tracking the wound

Simango,

Mushiri,

Yahya

et al. 2023

Preprint

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Due to uncontrolled bleeding in victims and frequently delayed emergency response times to road accidents had frequently causes severe casualties. To solve this problem, the robotic arm used in this paper, based on machine learning, is programmed to monitor and react to bleeding in accident victims. A clotting agent is applied to the wounds by the robotic arm at the touch of a button, stopping the bleeding and possibly saving lives. The system's image processing and wound classification were done in a Python-based Jupyter environment. SolidWorks was used to design the robotic arm, which was programmed to respond to input from a Python model. The robotic arm's kinematics was tested in the Simulink environment, displaying the joints' successful operation. The robotic arm design was further analyzed in the Simcape environment, where the arm's trajectory was evaluated. The results showed that the robotic arm could effectively move toward the detected wound, following the training trajectory. Object tracking was successfully performed in Matlab under the Simcape environment, as evidenced by the alignment between the expected and actual trajectory line graphs. The study concludes that the machine learning-based robotic arm can accurately move to any desired position within its workspace, enabling the precise application of the clotting agent on the wound. This system holds significant potential for improving emergency response times and outcomes in road accidents.

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