Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV)
Abstract
The subject matter described herein includes a modular and extensible approach to integrate noisy measurements from multiple heterogeneous sensors that yield either absolute or relative observations at different and varying time intervals, and to provide smooth and globally consistent estimates of position in real time for autonomous flight. We describe the development of the algorithms and software architecture for a new 1.9 kg MAV platform equipped with an IMU, laser scanner, stereo cameras, pressure altimeter, magnetometer, and a GPS receiver, in which the state estimation and control are performed onboard on an Intel NUC 3rd generation i3 processor. We illustrate the robustness of our framework in large-scale, indoor-outdoor autonomous aerial navigation experiments involving traversals of over 440 meters at average speeds of 1.5 m/s with winds around 10 mph while entering and exiting buildings.
- Inventors:
- Issue Date:
- Research Org.:
- Univ. of Pennsylvania, Philadelphia, PA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); US Office of Naval Research (ONR); National Science Foundation (NSF); US Air Force Office of Scientific Research (AFOSR)
- OSTI Identifier:
- 1735111
- Patent Number(s):
- 10732647
- Application Number:
- 15/684,700
- Assignee:
- The Trustees of the University of Pennsylvania (Philadelphia, PA)
- DOE Contract Number:
- 1138110; 113830; 1138847; FA9550-10-1-0567; N00014-07-1-0829; N00014-08-1-0696; N00014-09-1-1031; N00014-09-1-1051; W911NF-08-2-0004; W911NF-10-2-0016
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 08/23/2017
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Shen, Shaojie. Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV). United States: N. p., 2020.
Web.
Shen, Shaojie. Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV). United States.
Shen, Shaojie. Tue .
"Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV)". United States. https://www.osti.gov/servlets/purl/1735111.
@article{osti_1735111,
title = {Multi-sensor fusion for robust autonomous flight in indoor and outdoor environments with a rotorcraft micro-aerial vehicle (MAV)},
author = {Shen, Shaojie},
abstractNote = {The subject matter described herein includes a modular and extensible approach to integrate noisy measurements from multiple heterogeneous sensors that yield either absolute or relative observations at different and varying time intervals, and to provide smooth and globally consistent estimates of position in real time for autonomous flight. We describe the development of the algorithms and software architecture for a new 1.9 kg MAV platform equipped with an IMU, laser scanner, stereo cameras, pressure altimeter, magnetometer, and a GPS receiver, in which the state estimation and control are performed onboard on an Intel NUC 3rd generation i3 processor. We illustrate the robustness of our framework in large-scale, indoor-outdoor autonomous aerial navigation experiments involving traversals of over 440 meters at average speeds of 1.5 m/s with winds around 10 mph while entering and exiting buildings.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {8}
}
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