Collaborative Monocular Visual SLAM for Multi-Robot


  • Khandana Ali Khan Department of Computer Science, University of Balochistan, Quetta, Pakistan.
  • Shafaque Saira Malik Department of Computer Science, University of Balochistan, Quetta, Pakistan.



Micro aerial vehicle (MAV), Collaborative SLAM, ROS, Visual odometry


Collaborative SLAM is an amazing extension of single robot locations where multiple robots with monocular cameras work together in a dynamic environment to build one global map. The global map is later used by the multiple moving robots to localize themselves on the map. The application of collaborative SLAM can be used in various fields that include collaborative military tasks, search and rescue, agricultural planting, multi-robots working together to improve efficiency, and many others. 

Generally, every existing collaborative SLAM method uses an offline technique to process the collected data in the indoor environment. The indoor environment has limited space and lacks GPS connectivity. In this paper, we aim to give a step toward the usage of two drones equipped with monocular cameras and a standard laptop as the server for monitoring indoor workplaces. We worked on Simultaneous localization and mapping standard architecture with building the centralized global SLAM by the micro aerial vehicles such as Tello in our case. We investigated the method and localization of the drone on the global map.




How to Cite

Khandana Ali Khan, & Shafaque Saira Malik. (2022). Collaborative Monocular Visual SLAM for Multi-Robot. LC International Journal of STEM (ISSN: 2708-7123), 3(2), 19-30.