Papers › Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted...
Trajectory Prediction & Path Planning for an Object Intercepting UAV with a Mounted Depth Camera
Jasper Tan, Arijit Dasgupta, Arjun Agrawal, Sutthiphong Srigrarom
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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.
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