Xypher Bot: Autonomous Surveying Robot

Year : 2025 | Volume : 03 | Issue : 02 | Page : 49 62
    By

    Utkarsh Tripathi,

  • Manas Tripathi,

  • Sheetal Prajapati,

  • Dhyan Chandra Yadav,

  1. Student, Department of Computer Science & Engineering, Babu Banarasi Das University, Uttar Pradesh, India
  2. Assistant Professor, Department of Computer Science & Engineering, Babu Banarasi Das University, Uttar Pradesh, India
  3. Assistant Professor, Department of Computer Science & Engineering, Babu Banarasi Das University, Uttar Pradesh, India
  4. Assistant Professor, Department of Computer Science & Engineering, Babu Banarasi Das University, Uttar Pradesh, India

Abstract

Xypher Bot is a fully autonomous robot built to carry out tasks like height measurement, estimating distance, and detecting objects. It uses affordable and easily available components such as the MPU6050 sensor, ultrasonic sensors, and a laser pointer. By using simple trigonometry, the bot can measure object height with good accuracy. The top part of the bot, which is responsible for height measurement, has already been built and tested. The design and working plan for the lower body movement system are ready, but the actual hardware is yet to be built. This study talks about how the bot is made, how it works, and where it can be useful especially in surveying, monitoring the environment, and automation. A feature to send live data through a Telegram bot is also planned. The Xypher Bot addresses existing limitations through a combination of robotic mobility, real-time mapping sensors, and intelligent navigation algorithms. Equipped with LiDAR, GPS, and ultrasonic sensors, the robot autonomously traverses complex environments, collects high-resolution spatial data, and generates precise topographical maps. Its onboard AI-based path-planning and obstacle-avoidance systems ensure smooth and efficient operation without human intervention. The collected data can be seamlessly integrated with GIS and CAD platforms for advanced analysis and modeling. Experimental results demonstrate that the Xypher Bot significantly reduces survey time while improving accuracy and consistency compared to traditional methods. This innovation represents a step toward fully automated and intelligent surveying systems applicable in civil engineering, urban planning, mining, and environmental monitoring.

Keywords: Autonomous robot, height measurement, laser pointer, object detection, surveying

[This article belongs to International Journal of Advanced Robotics and Automation Technology ]

How to cite this article:
Utkarsh Tripathi, Manas Tripathi, Sheetal Prajapati, Dhyan Chandra Yadav. Xypher Bot: Autonomous Surveying Robot. International Journal of Advanced Robotics and Automation Technology. 2025; 03(02):49-62.
How to cite this URL:
Utkarsh Tripathi, Manas Tripathi, Sheetal Prajapati, Dhyan Chandra Yadav. Xypher Bot: Autonomous Surveying Robot. International Journal of Advanced Robotics and Automation Technology. 2025; 03(02):49-62. Available from: https://journals.stmjournals.com/ijarat/article=2025/view=232988


References

  1. Bradski G. The OpenCV library. Dr. Dobb’s J Softw Tools. 2000;120:122–5.
  2. Gonzalez RC, Woods R Digital Image Processing. 4th Edn. Pearson; New York. 2018.
  3. MPU-6000 and MPU-6050 product specification. Revision 3.4. Document No.: PS-MPU-6000A-00. San Jose (CA): InvenSense; 2013 Aug 19. Available from: https://robu.in/wp-content/uploads/2014/12/GY-87_EN.pdf.
  4. ELECFREAKS (2019). HC-SR04 Ultrasonic Module User Guide. [online] ELECFREAKS. Available from: https://www.elecfreaks.com/blog/post/hc-sr04-ultrasonic-module-user-guide.html.
  5. Infineon Technologies. (2024). BTS 7960: High current PN half bridge NovalithIC. [Online]. Data Sheet, Rev. 1.1. Neubiberg (Germany): Infineon Technologies. Available from: https://www.infineon
    .com/assets/row/public/documents/10/57/infineon-bts7960-ds-en.pdf
  6. (2025). Telegram Bot API. [Online] Telegram. Available from: https://core.telegram.org/
    bots/api.
  7. cc. (2025). Arduino Uno Board Specifications. [Online] Arduino. Available from: https://docs.arduino.cc/hardware/uno-rev3/.
  8. Hinton G, Deng L, Yu D, Dahl G, Mohamed A, Jaitly N, Senior A, Vanhoucke V, Nguyen P, Sainath T, Kingsbury B. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Process Mag. 2012;29(6):82–97. doi: 10.1109/MSP.2012.2205597.
  9. Marr D, Hildreth E. Theory of edge detection. Proc R Soc Lond B Biol Sci. 1980;207(1167):187–217. doi: 10.1098/rspb.1980.0020. PubMed PMID: 6102765.
  10. Ang JH, Min TS. A review on sensor technologies and control methods for mobile robot with obstacle detection system. Int J Robot Autom Sci. 2024 Apr 30;6(1):78–85.
  11. Yuan W, Li J, Bhatta M, Shi Y, Baenziger PS, Ge Y. Wheat height estimation using LiDAR in comparison to ultrasonic sensor and UAS. Sensors (Basel). 2018;18(11):3731. doi: 10.3390/s18113731. PubMed PMID: 30400154.
  12. Rahman A. Precision and accuracy of ultrasonic and infrared laser ToF IoT sensors. J Inform Telecommun Eng. 2025;8(2):219–26.
  13. Ušinskis V, Nowicki M, Dzedzickis A, Bučinskas V. Sensor-fusion based navigation for autonomous mobile robot. Sensors (Basel). 2025;25(4):1248. doi:10.3390/s25041248.
  1. Montemerlo M, Thrun S, Koller D, Wegbreit B. FastSLAM: A factored solution to the simultaneous localization and mapping problem. In: Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02); 2002 Jul 28–Aug 1; Edmonton, Alberta, Canada. Menlo Park (CA): AAAI Press; 2002. p. 593–8.
  2. Mur-Artal R, Tardos JD. ORB-SLAM2: An open-source SLAM system for monocular, stereo, and RGB-D cameras. IEEE Trans Robot. 2017;33(5):1255–62. doi: 10.1109/TRO.2017.2705103.
  3. Thrun S, Burgard W, Fox D. Probabilistic Robotics. Cambridge (MA): MIT Press; 2005.

 

 

 

 

 

 

Regular Issue Subscription Original Research
Volume 03
Issue 02
Received 15/09/2025
Accepted 15/10/2025
Published 25/10/2025
Publication Time 40 Days
71

Login


My IP

PlumX Metrics