@inproceedings{b8b2a33703ea4709a4e45c65b49cb6c2,
title = "Energy and time-efficient trajectory planning and geometric control for quadrotor waypoints flight",
abstract = "In recent years, there has been an increasing interest in studying motion planning algorithms for micro aerial vehicles (MAVs), especially quadrotors. Motion planning is an essential module to plan feasible motions that connect the initial and desired states while satisfying the required constraints. In this paper, we propose a new approach to trajectory planning for quadrotors using optimization techniques. Initially, to take full advantage of the actuators, we establish dynamic constraints by considering velocity and acceleration constraints in the formulation. Secondly, we create acceleration objectives based on heuristics that allow us to reduce flight time while still utilizing the highest possible acceleration. Next, we optimize the scaling of time allocation to arrive at a trajectory that is both efficient and feasible. Finally, a geometric tracking control is implemented to follow the planned trajectory. Our results demonstrate that this trajectory planning method exceeds the traditional minimum-snap trajectory.",
keywords = "control, optimization, quadrotor, trajectory",
author = "Ziniu Wu and Ruonan Zhang",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.",
year = "2023",
language = "English",
series = "International Conference on Control, Automation and Robotics (ICCAR)",
publisher = "IEEE",
pages = "273--278",
booktitle = "2023 9th International Conference on Control, Automation and Robotics, ICCAR 2023",
}