Presentation Title

3D Mapping and Integrated Collision Avoidance for Unmanned Aerial Vehicles

Faculty Mentor

Subodh Bhandari

Start Date

17-11-2018 8:30 AM

End Date

17-11-2018 10:30 AM

Location

HARBESON 62

Session

POSTER 1

Type of Presentation

Poster

Subject Area

engineering_computer_science

Abstract

This presentation discusses utilizing unmanned aerial vehicles (UAVs) and LiDAR technologies as a means for creating three-dimensional maps along with allowing for the detection of obstacles so that mid-air collisions may be avoided. This topic of research has many practical applications with disaster response being just one of them. Having a UAV safely navigate and produce an updated map of the affected area will serve as one invaluable piece of information that response teams will have at their disposal. A DJI S1000 Octocopter has been equipped with a Pixhawk, providing autonomous control of the UAV. A VLP-16 LiDAR along with an Xsens GPS aided inertial measurement unit (IMU) supply the data that is processed using an onboard Intel NUC board. The resulting data allows for a three-dimensional map to be created following post-processing using an Iterative Closest Point (ICP) algorithm and the CloudCompare software. The UAV was structurally modified to secure a 3D printed LiDAR mount at a 40˚ inclination which provides optimum results while keeping the center of gravity at an acceptable position. The open-source application, VeloView, was used for gathering LiDAR data for testing purposes. Work is currently underway to increase the accuracy of the created 3D maps with the combined LiDAR and IMU data. In addition, the integration of obstacle avoidance is being researched. More tests will be conducted using LiDAR and IMU data to increase the accuracy of the generated 3D maps. Simulated results captured with the VeloView application will be presented.

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Nov 17th, 8:30 AM Nov 17th, 10:30 AM

3D Mapping and Integrated Collision Avoidance for Unmanned Aerial Vehicles

HARBESON 62

This presentation discusses utilizing unmanned aerial vehicles (UAVs) and LiDAR technologies as a means for creating three-dimensional maps along with allowing for the detection of obstacles so that mid-air collisions may be avoided. This topic of research has many practical applications with disaster response being just one of them. Having a UAV safely navigate and produce an updated map of the affected area will serve as one invaluable piece of information that response teams will have at their disposal. A DJI S1000 Octocopter has been equipped with a Pixhawk, providing autonomous control of the UAV. A VLP-16 LiDAR along with an Xsens GPS aided inertial measurement unit (IMU) supply the data that is processed using an onboard Intel NUC board. The resulting data allows for a three-dimensional map to be created following post-processing using an Iterative Closest Point (ICP) algorithm and the CloudCompare software. The UAV was structurally modified to secure a 3D printed LiDAR mount at a 40˚ inclination which provides optimum results while keeping the center of gravity at an acceptable position. The open-source application, VeloView, was used for gathering LiDAR data for testing purposes. Work is currently underway to increase the accuracy of the created 3D maps with the combined LiDAR and IMU data. In addition, the integration of obstacle avoidance is being researched. More tests will be conducted using LiDAR and IMU data to increase the accuracy of the generated 3D maps. Simulated results captured with the VeloView application will be presented.