Prof.Tejjrao P Marode,Shripad M Chore,Nikhil A Zalte ,Gaurav V Vyavahare,Aditya R Raut

Autonomous rovers are crucial for navigating unknown environments in applications like planetary exploration and search-and-rescue missions. A key challenge is real-time localization and mapping, especially without GPS. This paper explores combining Visual-SLAM (Simultaneous Localization and Mapping) with LiDAR (Light Detection and Ranging) for rover localization, using the Robot Operating System (ROS) framework. By integrating data from an RGB-D camera and 360-degree LiDAR sensor, the rover can detect obstacles and map its surroundings. The system leverages ROS tools like Gazebo and Rviz for simulation and testing. The paper also discusses the integration of state-of-the-art algorithms for path planning and obstacle avoidance, and the fusion of visual and LiDAR data for more accurate environmental mapping. Results show that this fusion offers an efficient, GPS- independent solution for autonomous navigation in complex environments.

https://doi.org/10.58357/jedcs.2025.v4.i2.1