.png){kind=icon}
.png){kind=icon}
Return
Optimal autonomous multirotor motion planning in an obstructed environment
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ast.2019.03.017.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper addresses a methodology for autonomous motion planning of multirotor aircraft in obstructed environments. The control strategy allows the vehicle to online generate quasi-optimal trajectories with limited computational load while performing collision avoidance tasks. The problem is formulated in a model-predictive control architecture in which motion planning and trajectory tracking processes are solved separately. The first process is based on a spline path planning approach to generate smooth and safe trajectories. The second process elaborates trajectory inputs in terms of commanded thrust magnitude and desired attitude rates in order to steer the vehicle during the mission task. Results of both numerical simulations and, for the first time, an experimental validation are provided in order to assess the performance of the approach in the presence of external disturbances and unmodeled dynamics, provided adequate time horizon and update frequency are selected for the numerical optimization algorithm. (C) 2019 Elsevier Masson SAS. All rights reserved.
Keywords:
FLIGHT CONTROL
PATH
STABILIZATION
FLATNESS
TRACKING
VEHICLE
SYSTEMS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.8
Papers:
1.0W
Citations:
3.0W