Localization and Navigation in Mobile Robots
School Name
South Carolina Governor's School for Science and Mathematics
Grade Level
12th Grade
Presentation Topic
Engineering
Presentation Type
Mentored
Abstract
With robotics only becoming more prominent it is important to know how these systems orient themselves in space and move around. Navigation and localization were explored and implemented initially by using an Arduino Mobile Rover. Using MATLAB and Simulink to control the rover, algorithms were used to calculate waypoints within an arena and allow the robot to move toward a target. The robot adjusts to find these markers and inches toward its goal. To learn more about how computer vision allows robots to know what environment they are in, maps were created using a LiDAR sensor. Using laser pulsing, LiDAR can create a variety of maps. Just a few examples of its mapping capabilities are 3D models, terrain maps, elevation maps, canopy height maps, and more. For this project, the basic mapping function of LiDAR was used to find the perimeter of the surrounding area. Objects were placed in the environment to further demonstrate how the sensor works. Ultimately, robots require data from not just one, but multiple sensors so that they can move correctly within space and fulfill their purpose. LiDAR helps fulfill this greater goal.
Recommended Citation
Voulgaris, Sophia, "Localization and Navigation in Mobile Robots" (2024). South Carolina Junior Academy of Science. 447.
https://scholarexchange.furman.edu/scjas/2024/all/447
Location
RITA 273
Start Date
3-23-2024 10:00 AM
Presentation Format
Oral Only
Group Project
No
Localization and Navigation in Mobile Robots
RITA 273
With robotics only becoming more prominent it is important to know how these systems orient themselves in space and move around. Navigation and localization were explored and implemented initially by using an Arduino Mobile Rover. Using MATLAB and Simulink to control the rover, algorithms were used to calculate waypoints within an arena and allow the robot to move toward a target. The robot adjusts to find these markers and inches toward its goal. To learn more about how computer vision allows robots to know what environment they are in, maps were created using a LiDAR sensor. Using laser pulsing, LiDAR can create a variety of maps. Just a few examples of its mapping capabilities are 3D models, terrain maps, elevation maps, canopy height maps, and more. For this project, the basic mapping function of LiDAR was used to find the perimeter of the surrounding area. Objects were placed in the environment to further demonstrate how the sensor works. Ultimately, robots require data from not just one, but multiple sensors so that they can move correctly within space and fulfill their purpose. LiDAR helps fulfill this greater goal.