TY - GEN
T1 - Target-visible Polynomial Trajectory Generation within an MAV Team
AU - Lee, Yunwoo
AU - Park, Jungwon
AU - Jeon, Boseong
AU - Kim, H. Jin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85124339492
U2 - 10.1109/IROS51168.2021.9636446
DO - 10.1109/IROS51168.2021.9636446
M3 - Conference contribution
AN - SCOPUS:85124339492
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 1982
EP - 1989
BT - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Y2 - 27 September 2021 through 1 October 2021
ER -