TPL: Trajectory Planner for Target Tracking in Low-Light Environments

Abstract

Unmanned Aerial Vehicles (UAVs) have drawn attention in recent years due to the wide spectrum of utilization. Out of those areas, autonomous aerial tracking is one of the fields that could be applied widely. The main purpose of this paper is to develop a novel trajectory planner for autonomous aerial tracking that is feasible even in areas where light is scarce. The poor lighting condition is handled by equipping and utilizing a thermal camera and a Time-of-Flight (ToF) camera on the UAV. In addition, minimum snap trajectory is adopted to track the target and kinodynamics of the UAV is considered at the same time, which is optimized by solving a quadratic programming with corridor constraints considering the noises of the cameras. Moreover, based on the former information, the proposed system predicts the future motion of the target considering dynamic constraints. The performance of the proposed approach is validated by intensive simulations and real-world experiments.