Please use this identifier to cite or link to this item: https://doi.org/10.23919/ICCAS52745.2021.9649912
Title: Trajectory Prediction Path Planning for an Object Intercepting UAV with a Mounted Depth Camera
Authors: Tan, J
Dasgupta, A
Agrawal, A
Srigrarom, S 
Issue Date: 1-Jan-2021
Publisher: IEEE
Citation: Tan, J, Dasgupta, A, Agrawal, A, Srigrarom, S (2021-01-01). Trajectory Prediction Path Planning for an Object Intercepting UAV with a Mounted Depth Camera. 2021 21st International Conference on Control, Automation and Systems (ICCAS) 2021-October : 703-708. ScholarBank@NUS Repository. https://doi.org/10.23919/ICCAS52745.2021.9649912
Abstract: A novel control software architecture using ROS C++ is introduced for object interception by a UAV with a mounted depth camera and no external aid. Existing work in trajectory prediction focused on the use of off-board tools like motion capture rooms to intercept thrown objects. The present study designs the UAV architecture to be completely on-board capable of object interception with the use of a depth camera and point cloud processing. The architecture uses an iterative trajectory prediction algorithm for non-propelled objects like a ping-pong ball. A variety of path planning approaches to object interception and their corresponding scenarios are discussed, evaluated simulated in Gazebo. The successful simulations exemplify the potential of using the proposed architecture for the onboard autonomy of UAVs intercepting objects.
Source Title: 2021 21st International Conference on Control, Automation and Systems (ICCAS)
URI: https://scholarbank.nus.edu.sg/handle/10635/217716
ISBN: 9788993215212
ISSN: 15987833
DOI: 10.23919/ICCAS52745.2021.9649912
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