(IROS) Target-visible Polynomial Trajectory Generation within an MAV Team

Abstract: Autonomous aerial videography is a challenging task, which involves collision avoidance against obstacles and visibility guaranteed target tracking in unstructured environments. In this paper, we organize a two micro aerial vehicle (MAV) team, which consists of a target agent responsible for a specific mission and a camera agent for filming the target agent. Especially, this paper focuses on trajectory planning of the camera agent to chase without occlusion of target agent. Our trajectory planner module includes two phases of guaranteeing target visibility. In the first phase, we generate homotopic safe flight corridor (SFC) to attain target-visible regions. In the subsequent phase, we generate a safe and smooth trajectory with the continuous visibility constraint based on the SFC, using quadratic programming (QP). Regardless of complexity of map, our planner converts an overall problem to a single QP and generates a steady flight trajectory without undesirable fluctuating motion, while guaranteeing all-time visibility. We validate our approach in Gazebo simulations and a real-world experiment.

Bibtex

@INPROCEEDINGS{9636446,
  author={Lee, Yunwoo and Park, Jungwon and Jeon, Boseong and Kim, H. Jin},
  booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 
  title={Target-visible Polynomial Trajectory Generation within an MAV Team}, 
  year={2021},
  volume={},
  number={},
  pages={1982-1989},
  keywords={Target tracking;Trajectory planning;Cameras;Complexity theory;Quadratic programming;Task analysis;Collision avoidance},
  doi={10.1109/IROS51168.2021.9636446}}