Tracking a moving target in cluttered environments using a quadrotor
We address the challenging problem of tracking a moving target in cluttered environments using a quadrotor. Our online trajectory planning method generates smooth, dynamically feasible, and collision free polynomial trajectories that follow a visually tracked moving target. As visual observations of the target are obtained, the target trajectory can be estimated and used to predict the target motion for a short time horizon. We propose a formulation to embed both limited horizon tracking error and quadrotor control costs in the cost function for a quadratic programming (QP) while encoding both collision avoidance and dynamical feasibility as linear inequality constraints for the QP. Our method generates tracking trajectories in the order of milliseconds and is therefore suitable for online target tracking with a limited sensing range. We implement our approach on board a quadrotor testbed equipped with cameras, a laser range finder, an IMU, and onboard computing. Statistical analysis, simulation, and real world experiments are conducted to demonstrate the effectiveness of our approach.
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)