Development Of a Waypoint Navigation System For Rvm Robots Using Path Planning Algorithms
- DOI
- 10.2991/978-94-6463-678-9_41How to use a DOI?
- Keywords
- Robot RVM; Navigationi Waypoint; Image Processing; YOLOv7
- Abstract
This research aims to develop and test a RVM navigation system using waypoint-based path planning method. In this study, YOLOv7 is used to detect the robot with the help of a webcam mounted on the ceiling of the room. The robot is equipped with red and green dots on it, where the red dot signifies the front and the green dot the back, thus allowing determination of the robot's orientation. The system allows the user to specify the waypoint that the robot should reach. The motor movement data is sent to Firebase once the coordinates of the robot and the waypoint destination are determined. NodeMCU then retrieves the data and sends it to Arduino which controls the motor driver to move the robot towards the waypoint. The test results show that the navigation system successfully directs the robot to the waypoint appropriately. The conclusion of this research shows that the designed navigation system is successful and stable in directing the robot to the predetermined waypoint.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Selamat Muslimin AU - Ekawati Prihatini AU - Nyayu Latifah Husni AU - Satria Pebrian PY - 2025 DA - 2025/05/01 TI - Development Of a Waypoint Navigation System For Rvm Robots Using Path Planning Algorithms BT - Proceedings of the 8th FIRST 2024 International Conference on Global Innovations (FIRST-ESCSI 2024 ) PB - Atlantis Press SP - 428 EP - 442 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-678-9_41 DO - 10.2991/978-94-6463-678-9_41 ID - Muslimin2025 ER -