Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted Depth Camera
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 on-board autonomy of UAVs intercepting objects.
Cite
@article{arxiv.2111.09083,
title = {Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted Depth Camera},
author = {Jasper Tan and Arijit Dasgupta and Arjun Agrawal and Sutthiphong Srigrarom},
journal= {arXiv preprint arXiv:2111.09083},
year = {2021}
}
Comments
Accepted at the 21st International Conference on Control, Automation and Systems 2021 (ICCAS 2021)