Vision-Based Guidance for Tracking Dynamic Objects
This addresses the challenge of reliable object tracking for unmanned aircraft systems, but appears incremental as it builds on existing guidance and feature point methods.
The paper tackles the problem of tracking dynamic objects with a vision-based framework using guidance laws, enabling an unmanned aircraft system to continuously follow a moving object within a monocular camera's field of view, with simulations demonstrating efficacy.
In this paper, we present a novel vision-based framework for tracking dynamic objects using guidance laws based on a rendezvous cone approach. These guidance laws enable an unmanned aircraft system equipped with a monocular camera to continuously follow a moving object within the sensor's field of view. We identify and classify feature point estimators for managing the occurrence of occlusions during the tracking process in an exclusive manner. Furthermore, we develop an open-source simulation environment and perform a series of simulations to show the efficacy of our methods.