Design and Implementation of an IoT-Based 4-DOF Wi-Fi Controlled Robotic Arm using ESP32 and Blynk Cloud
DOI:
https://doi.org/10.69968/6w3jr198Keywords:
Internet of Things (IoT), ESP32, 4-DOF Robotic Arm, Blynk Cloud, Real-time Automation, Kinematics, Wireless Control, Cyber-Physical Systems, Industry 4.0Abstract
The rapid evolution of Industry 4.0 has necessitated the development of highly adaptable, remotely operable cyber-physical systems. Among these, robotic manipulators play a pivotal role in handling hazardous materials, precision manufacturing, and remote intervention tasks. This research presents the comprehensive design, mathematical modeling, and implementation of a 4-Degree of Freedom (4-DOF) robotic arm integrated with Internet of Things (IoT) capabilities. Utilizing the high-performance, dual-core ESP32 microcontroller, the system overcomes the traditional spatial limitations of localized Radio Frequency (RF) and Bluetooth controllers by leveraging Wi-Fi connectivity to achieve global remote teleoperation. Actuation is achieved through a network of precision servo motors, carefully calibrated via high-resolution Pulse Width Modulation (PWM) signals generated by the ESP32. The user interface is deployed via the Blynk Cloud platform, establishing a low-latency, bidirectional MQTT/HTTP communication bridge between a smartphone application and the physical hardware. The primary objectives of this study are to evaluate the latency constraints of cloud-based robotics, formulate the Forward Kinematics utilizing Denavit-Hartenberg (D-H) parameters, and validate the mechanical reliability of a low-cost 4-DOF manipulator under varying network conditions. Experimental results demonstrate a highly responsive system with an average network latency of less than 45 milliseconds on standard high-speed broadband, alongside excellent joint interpolation and repeatable end-effector positioning. Ultimately, this research provides a scalable, cost-effective framework for educational, laboratory, and lightweight industrial remote manipulation, effectively demonstrating the convergence of IoT cloud architecture and mechanical actuation
References
1]
A. Smith, B. Johnson, and C. Lee, "Bluetooth-based localized teleoperation for lightweight robotic manipulators," IEEE Trans. Ind. Electron., vol. 68, no. 4, pp. 3120-3129, Apr. 2021.
[2]
D. Jones and X. Wang, "Performance evaluation of low-power wireless protocols in robotics," IEEE/ASME Trans. Mechatronics, vol. 25, no. 2, pp. 845-854, 2020.
[3]
R. Kumar, T. Singh, and M. Patel, "Zigbee integrated mesh networking for agricultural robotic swarms," in Proc. IEEE Int. Conf. Robot. Autom. (ICRA), 2022, pp. 412-418.
[4]
S. Lee and J. Kim, "Wi-Fi enabled automated guided vehicles for smart warehousing," IEEE Access, vol. 9, pp. 112345-112355, 2021.
[5]
V. Patel, K. Sharma, and A. Desai, "A comparative study of MQTT and CoAP protocols for IoT-based robotic control," IEEE Internet Things J., vol. 8, no. 15, pp. 12050-12061, 2021.
[6]
S. Gupta, "Bottlenecks in 8-bit microcontrollers for complex JSON parsing in IoT robotics," Int. J. Embed. Syst., vol. 14, no. 3, pp. 210-218, 2022.
[7]
M. Chen and L. Zhang, "Linux-based task scheduling latency in Raspberry Pi robotic applications," IEEE Trans. Cybern., vol. 53, no. 1, pp. 154-164, 2023.
[8]
J. Martinez, A. Lopez, and C. Garcia, "Exploiting FreeRTOS on ESP32 for deterministic robotic actuation," IEEE Embedded Syst. Lett., vol. 14, no. 2, pp. 45-49, 2022.
[9]
T. Nguyen and P. Tran, "Node-RED visual programming for industrial IoT applications," in Proc. IEEE Ind. Cyber-Phys. Syst. (ICPS), 2021, pp. 78-83.
[10]
A. Rahman, "Rate-limiting impacts of ThingSpeak on real-time mechatronic systems," J. Sens. Actuator Netw., vol. 10, no. 4, p. 65, 2021.
[11]
K. Nirav, P. Het, and N. Tarunkumar, "Evaluating Blynk cloud infrastructure for low-latency hardware control," IEEE Access, vol. 10, pp. 55670-55682, 2022.
[12]
S. Rane and M. Shanmugavel, "Mobile-first GUI paradigms for robotic teleoperation," IEEE Trans. Human-Mach. Syst., vol. 54, no. 3, pp. 310-319, 2024.
[13]
R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza, Introduction to Autonomous Mobile Robots, 3rd ed. Cambridge, MA, USA: MIT Press, 2023.
[14]
J. Craig, Introduction to Robotics: Mechanics and Control, 4th ed. Pearson, 2022.
[15]
A. Goswami and P. Vadakkepat, "Kinematic modeling of a 4-DOF manipulator using Denavit-Hartenberg parameters," in Proc. IEEE Int. Conf. Adv. Robot., 2021, pp. 234-240.
[16]
Espressif Systems, "ESP32 Series Datasheet," V4.1, 2023. [Online]. Available: https://www.espressif.com.
[17]
Y. Zhao, W. Li, and H. Wang, "Design of dual-core microcontroller systems for simultaneous wireless communication and motor control," IEEE Trans. Ind. Appl., vol. 58, no. 5, pp. 6120-6128, 2022.
[18]
C. Ahn and M. Kang, "Analysis of back-EMF effects on IoT edge devices during high-torque servo actuation," IEEE Trans. Power Electron., vol. 37, no. 8, pp. 9340-9351, 2022.
[19]
P. Kumar, "LM2596 buck converter efficiency optimization for battery-operated robotic nodes," IEEE J. Emerg. Sel. Topics Power Electron., vol. 10, no. 2, pp. 1450-1459, 2022.
[20]
F. Silva, D. Costa, and J. Oliveira, "Implementation of watchdogs and failsafe mechanisms in wireless embedded systems," IEEE Trans. Rel., vol. 71, no. 1, pp. 120-128, 2022.
[21]
G. Antonelli, "Network latency constraints in tele-robotics over public internet infrastructure," IEEE Commun. Mag., vol. 60, no. 9, pp. 54-60, 2022.
[22]
S. B. Niku, Introduction to Robotics: Analysis, Control, Applications, 3rd ed. Wiley, 2020.
[23]
H. Patel, M. Joshi, and S. Shah, "Cost-effective IoT frameworks for educational mechatronics laboratories," IEEE Trans. Educ., vol. 65, no. 4, pp. 410-418, 2022.
[24]
Z. Li, C. Ge, and S. Zhao, "Trajectory planning for multi-DOF manipulators under cloud computing architectures," IEEE Trans. Autom. Sci. Eng., vol. 19, no. 3, pp. 2105-2115, 2022.
[25]
W. Zhang, "Jitter analysis in pulse width modulation signals for robotic servo control," IEEE Sens. J., vol. 22, no. 11, pp. 10450-10458, 2022.
[26]
E. Garcia and R. Perez, "Security vulnerabilities in MQTT-based robotic teleoperation systems," IEEE Trans. Dependable Secure Comput., vol. 20, no. 2, pp. 880-891, 2023.
[27]
T. Kim, "Development of a 3D printable 4-DOF manipulator for rapid prototyping," Addit. Manuf., vol. 47, p. 102250, 2021.
[28]
L. Wang, "Industry 4.0: The role of edge computing in smart manufacturing," IEEE Ind. Electron. Mag., vol. 16, no. 1, pp. 24-34, 2022.
[29]
A. K. Singh and V. Kumar, "Torque and payload optimization in small-scale robotic arms," Int. J. Adv. Manuf. Technol., vol. 121, pp. 3401-3415, 2022.
[30]
Blynk Inc., "Blynk IoT Platform Documentation," 2024. [Online]. Available: https://docs.blynk.io.
[31]
M. Rossi, "Comparative study of Arduino and ESP32 for high-frequency PWM applications," IEEE Access, vol. 11, pp. 15020-15031, 2023.
[32]
S. Nakamura, "Future perspectives on voice-actuated cyber-physical systems," IEEE Trans. Human-Mach. Syst., vol. 53, no. 6, pp. 1020-1030, 2023.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Nayak Tarunkumar Kiritbhai, Sujit Rohit, Naitik Patel, Jogesh Chaudhari, Ashish Pandey, Apexa Purohit, Mayur Chavda, Patel Het Bhikhabhai, Kachhiya Nirav Pravinbhai, Mayank Dev Singh
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Re-users must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. This license allows for redistribution, commercial and non-commercial, as long as the original work is properly credited.
How to Cite
7
