Name
Title | ||
|---|---|---|
Robust multi-sensor fusion for micro aerial vehicle navigation in GPS-degraded/denied environments |
Abstract | ||
|---|---|---|
State estimation for Micro Air Vehicles (MAVs) is challenging because sensing instrumentation carried on-board is severely limited by weight and power constraints. In addition, their use close to and inside structures and vegetation means that GPS signals can be degraded or all together absent. Here we present a navigation system suited for use on MAVs that seamlessly fuses any combination of GPS, visual odometry, inertial measurements, and/or barometric pressure. We focus on robustness against real-world conditions and evaluate performance in challenging field experiments. Results demonstrate that the proposed approach is effective at providing a consistent state estimate even during multiple sensor failures and can be used for mapping, planning, and control. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ACC.2014.6859341 | American Control Conference |
Keywords | Field | DocType |
Global Positioning System,autonomous aerial vehicles,distance measurement,image fusion,microrobots,mobile robots,path planning,robot vision,state estimation,GPS signals,GPS-degraded environments,GPS-denied environments,MAV,barometric pressure,inertial measurements,micro aerial vehicle navigation,power constraint,robust multisensor fusion,sensing instrumentation,state estimation,visual odometry,weight constraint,Autonomous systems,Filtering,Vision-based control | Computer vision,Visual odometry,Computer science,Navigation system,Sensor fusion,Control engineering,Robustness (computer science),Artificial intelligence,Global Positioning System,Fuse (electrical),GPS signals,Instrumentation | Conference |
ISSN | Citations | PageRank |
0743-1619 | 8 | 0.60 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chambers, A. | 1 | 8 | 0.60 |
| Sebastian Scherer | 2 | 522 | 57.76 |
| Yoder, L. | 3 | 8 | 0.60 |
| Jain, S. | 4 | 13 | 1.08 |