Abstract
Simultaneous Localisation and Mapping (SLAM) is the mapping of an unknown environment and at the same time localising the ego body in that environment. ORB SLAM2 (IEEE Trans Robot 33:1255–1262 2017 [1]) is a state of the art visual SLAM algorithm which can calculate camera trajectory using Monocular camera. Since monocular slam has the scale drift issue the source code has been so altered that the map can be saved or previously built map can be reloaded for localisation. To plan optimal trajectory of a vehicle to reach from a source to goal, A* (Computing the shortest path: A search meets graph theory 2005 [2]) search algorithm has been implemented. Gazebo (2004 IEEE/RSJ International Conference on Intelligent Robots and Systems 2004 [3]) is an open-source robot simulation tool on which a Turtlebot robot was used to test algorithm that has been proposed in this paper. Turtlebot is a two-wheeled differential drive robot on which various sensors are mounted. A novel approach has been used for local path planning of the vehicle. ROS (ROS: an open-source Robot Operating System 2009 [4]) framework has been used to communicate between various nodes for performing navigation.
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Vithalani, S., Soni, S., Rajpura, P. (2020). Autonomous Navigation Using Monocular ORB SLAM2. In: Mehta, A., Rawat, A., Chauhan, P. (eds) Recent Advances in Communication Infrastructure. Lecture Notes in Electrical Engineering, vol 618. Springer, Singapore. https://doi.org/10.1007/978-981-15-0974-2_6
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