PATH PLANNING IN SLAM
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Date
2024-05-03
Authors
Bazylkhanov, Mukhtar
Sultan, Aida
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
Simultaneous Localization and Mapping (SLAM) is a technology that helps an
autonomous robot to localize itself in the unknown environment creating a map
and further navigating without any human interference. Within the SLAM tech-
nology we are able to make detailed maps of the environment both in outdoor and
indoor spaces where GPS signals are not available. Overall, SLAM is highly effi-
cient technology that can help robots to properly navigate, inspect and monitor
industrial environments autonomously through proper path planning. Identify-
ing the shortest collision-free path and bypassing obstacles quickly is done by
path-planning that applies different algorithms and their combinations. Due to
the challenging environments, sensor limitations and discrepancies in localization
estimation, it can be hard for robots to efficiently bypass and arrive at the desired
destination. Therefore in our thesis we aim to familiarize ourselves with the path
planning algorithms to fit the turtlebot. Our research focuses on individually ex-
amining the pivotal path planning algorithms ( Djikstra, A* and RRT) to test
it in the application of turtlebot to identify which algorithm is suitable for this
robotic device. The research is done by analyzing existing literature on path-
planning to further apply the knowledge in an experiment. It was found that
despite the better intrinsic capabilities of A* and RRT algorithms, the Dijkstra
appears to be the most advisable algorithm for the turtlebot ).
Description
Keywords
Type of access: Restricted, Path planning, Dijkstra, A*, A-star, RRT, Turtlebot, Indoor mobile robots, Mobile robots, SLAM
Citation
Bazylkhanov, M., Sultan, A. (2024). Path Planning in SLAM. Nazarbayev University School of Engineering and Digital Sciences