Use of Small Arrays of Single Beam Laser Rangefinders for Intelligent Vehicle Obstacle Detection and Point Cloud Development
Location
Room 2911
Session Format
Paper Presentation
Research Area Topic:
Engineering and Material Sciences - Mechanical
Abstract
Ground vehicles with autonomous navigation require medium range external sensing for early obstacle detection and terrain mapping. Both are essential for path planning. The conventional method for accomplishing this is achieved by very complex and expensive LiDAR sensors with 32 to 64 individual lasers rotating rapidly and taking readings from the top of the vehicle. Our most pertinent research question however is to ascertain if a less cumbersome and cost effective setup of a small number of single beam laser rangefinder sensors can accomplish the same task. Our current method to achieve this is to sweep the sensors a variable number of steps along a predetermined angle. The information obtained is used to develop a complete and detailed view of the world around the intelligent vehicle. Lasers sensors are the most viable type of sensors for this process due to low interference and long range accuracy data can be obtained with reasonable power consumption. This paper is focused on a small laser ranger finder attached to a programmable pan-tilt mount positioned at the front of the intelligent vehicle. The sensors and mount are connected to a micro-controller which gathers position and distance information of significant objects in the path of the vehicle, in polar coordinates. This information is then converted to more useful Cartesian coordinates and plotted on a point cloud which is then used for path planning in real time. The greatest advantage of this system is that it is built to use minimal processing space and can be controlled entirely by a micro-controller, leaving valuable space and power for other important aspects of the intelligent vehicle. Future work will include sensor fusion of this system and an image sensor for detection of relevant objects such as traffic signs. Such systems establish a distance from the vehicle as well as distinguish them by shape and color.
Presentation Type and Release Option
Presentation (Open Access)
Start Date
4-16-2016 4:00 PM
End Date
4-16-2016 5:00 PM
Recommended Citation
Ibru, Benard Ogheneovo, "Use of Small Arrays of Single Beam Laser Rangefinders for Intelligent Vehicle Obstacle Detection and Point Cloud Development" (2016). GS4 Georgia Southern Student Scholars Symposium. 57.
https://digitalcommons.georgiasouthern.edu/research_symposium/2016/2016/57
Use of Small Arrays of Single Beam Laser Rangefinders for Intelligent Vehicle Obstacle Detection and Point Cloud Development
Room 2911
Ground vehicles with autonomous navigation require medium range external sensing for early obstacle detection and terrain mapping. Both are essential for path planning. The conventional method for accomplishing this is achieved by very complex and expensive LiDAR sensors with 32 to 64 individual lasers rotating rapidly and taking readings from the top of the vehicle. Our most pertinent research question however is to ascertain if a less cumbersome and cost effective setup of a small number of single beam laser rangefinder sensors can accomplish the same task. Our current method to achieve this is to sweep the sensors a variable number of steps along a predetermined angle. The information obtained is used to develop a complete and detailed view of the world around the intelligent vehicle. Lasers sensors are the most viable type of sensors for this process due to low interference and long range accuracy data can be obtained with reasonable power consumption. This paper is focused on a small laser ranger finder attached to a programmable pan-tilt mount positioned at the front of the intelligent vehicle. The sensors and mount are connected to a micro-controller which gathers position and distance information of significant objects in the path of the vehicle, in polar coordinates. This information is then converted to more useful Cartesian coordinates and plotted on a point cloud which is then used for path planning in real time. The greatest advantage of this system is that it is built to use minimal processing space and can be controlled entirely by a micro-controller, leaving valuable space and power for other important aspects of the intelligent vehicle. Future work will include sensor fusion of this system and an image sensor for detection of relevant objects such as traffic signs. Such systems establish a distance from the vehicle as well as distinguish them by shape and color.
