Mrudula Kandalkar,
Arya Deshpande,
Sakshi Kulkarni,
- Student, SKN College of Engineering, SPPU, Pune, Maharashtra, India
- Student, SKN College of Engineering, SPPU, Pune, Maharashtra, India
- Student, SKN College of Engineering, SPPU, Pune, Maharashtra, India
Abstract
In the past few years, robotics technology has made remarkable progress. In order to assist humans in their work, robots that can recognise and track people are required; as a result, tools like the “Human Following Load carrier” that can converse and live with people must be created. Localising the robot and its surroundings is one of the primary obstacles in enabling the robot to do different jobs in the real world. A robot needs to have sophisticated navigational abilities in order to track a person through traffic, in busy regions, and in both indoor and outdoor environments. The following robot, which can carry objects in addition to humans, is what the project aims to build. It can be used in farms, shopping malls, building sites, and airports. Ultrasonic sensors detect the human target’s presence and distance, with the Raspberry Pi Pico processing this data to determine the target’s position. An algorithm adjusts the robot’s speed and direction through pulse-width modulation (PWM) signals to the DC motors. The integration of the Raspberry Pi Pico with the sensors and motors is optimized for precise control and reliable performance. Testing in various indoor scenarios demonstrates the robot’s ability to consistently follow a human target and navigate around obstacles effectively. Future enhancements will focus on system robustness, advanced sensor fusion techniques, and outdoor functionality. A microcontroller, or microprocessor, is the device that runs the entire system.
Keywords: Human following, Trolley, Raspberry Pi Pico, Sensors, Obstacles avoidance.
References
- Ashutosh Gujar, Kalyanee Jadhav, “Bluetooth Based and GPS Based Follow Me Robot”, International Research Journal of Engineering and Technology (IRJET), April 2021. Volume: 08 Issue: 04 | Apr 2021
- B. Akbar, D. G. Taylor and G. D. Durgin, “Two-Dimensional Position and Orientation Estimation Using a 5.8 GHz RFID System,” in IEEE Journal of Radio Frequency Identification, vol. 4, no. 4, pp. 365-372, Dec. 2020, doi: 10.1109/JRFID.2020.3015807.
- Qian Ma , Xia Li, Guanyu Li, Bo Ning, Mei Bai and Xite Wang, “Mobile RFID-Based Localization for Indoor Human Tracking”, Sensors2020, 20(6), 1711; https://doi.org/10.3390/s20061711
- Muhammad Sarmad Hassan, Mafaz Wali Khan, “Design and Development of Human Following Robot”, Student Research Paper Conference., vol. 2, no. 15, July 2015.
- Thennavarajan Subramanian, Rahul Madbhavi, Shreepad Potadar, Sylvester Jerome D’souza, K V Gangadharan, “Object Follower and Barrier Escaping Robot Using Image Processing”, International Journal of Innovative Research in Science, Engineering and Technology., Vol. 4, Issue 7, July 2015.
- W. Tai, B. Ilias , S.A. Abdul Shukor, N. Abdul Rahim, “A Study of Ultrasonic Sensor Capability in Human Following Robot System”, IOP Conf. Ser.: Mater. Sci. Eng.705 012045.
- Kim, Myungsik, Chong, Nak Young, Ahn, Hyo-Sung, Yu, Wonpil, “RFID-enabled Target Tracking and Following with a Mobile Robot Using Direction Finding Antennas”, IEEE International Conference on Automation Science and Engineering., 2007.
- Ileni Abhinav Theja, Gudur Chandrakanth, Ravvula Akhil, Shaik Areef, “Human Following Robot”, International Journal of Advance Research, Ideas and Innovations in Technology., vol. 7.
- Huang TY, Gu H, Nelson BJ. Increasingly intelligent micromachines. Annual Review of Control, Robotics, and Autonomous Systems. 2022 May 3;5(1):279-310.
- Molina A, Rodriguez CA, Ahuett H, Cortés JA, Ramírez M, Jiménez G, Martinez S. Next-generation manufacturing systems: key research issues in developing and integrating reconfigurable and intelligent machines. International Journal of Computer Integrated Manufacturing. 2005 Oct 1;18(7):525-36.
- Bandari VK, Schmidt OG. System‐Engineered Miniaturized Robots: From Structure to Intelligence. Advanced Intelligent Systems. 2021 Oct;3(10):2000284.
Journal of Nuclear Engineering & Technology
| Volume | |
| Received | July 1, 2024 |
| Accepted | July 31, 2024 |
| Published | August 16, 2024 |