Name
Abstract | ||
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Autonomous control of ultra-light indoor microfly- ers is a difficult and largely unsolved task because of the strong limitations on the kind of sensors that can be embedded. We propose a new approach for altitude control of a 10-gram microflyer, where altitude as well as pitch angle are estimated using a set of visual, airspeed and gyroscopic sensors that weight about 1 (g) in total. This approach does not rely on an explicit estimation of optic flow, but rather takes as input the raw images as provided by the vision sensor. We show that altitude and pitch angle of a simulated agent can be successfully estimated. This result is thus a first step toward autonomous altitude control of indoor flying robots. I. INTRODUCTION Autonomous indoor flight poses a number of challenges that are yet to be solved. Unlike outdoor drones, the weight constraint precludes the use of many sensors. High precision inertial measurement units (IMU) are too heavy to be em- bedded on ultra-light microflyers, GPS signals are unavailable indoors and the horizon cannot be used as visual absolute angular reference. In general, active sensors, like distance sensors, tend to consume too much energy, as opposed to passive sensors such as simple CMOS cameras, MEMS rate gyros and anemometers. It is interesting to note that the fly seems to use the same kind of sensory modalities for navigation. The most important one is vision (1), (2), but gyroscopic information is also available thanks to organs called halteres (3), and it is probably the case for airspeed by the means of hairs and antennas (4). It has been suggested that basic control of an indoor microflyer can be reduced to a minimal set of four behaviors1: attitude control (ATC), course stabilization (CS), obstacle avoidance (OA) and altitude control (ALC) (5), (6). ATC consists of keeping the airplane roll and pitch angles stable. CS forces the airplane into straight or, at least, controlled trajectories when flying in free spaces, while OA ensures that it will not collide with walls and other obstacles. Finally, ALC keeps the airplane at proper altitude over ground or obstacles. Implementation of the first three of these behaviors has already been demonstrated with a 30-gram airplane (7). ATC was for the most part passively stabilized by the airplane |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ROBOT.2006.1642131 | Orlando, FL |
Keywords | Field | DocType |
aerospace robotics,aircraft control,height measurement,image sensors,microrobots,mobile robots,spatial variables control,airspeed sensor,autonomous altitude control,gyroscopic sensors,pitch estimation,ultra-light indoor microflyers,vision sensor,vision-based altitude estimation | Computer vision,Pitch angle,Image sensor,Intelligent sensor,Altitude,Control engineering,Automatic control,Artificial intelligence,Engineering,Airspeed,Robot,Mobile robot | Conference |
Volume | Issue | ISSN |
2006 | 1 | 1050-4729 |
ISBN | Citations | PageRank |
0-7803-9505-0 | 4 | 0.96 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antoine Beyeler | 1 | 173 | 17.54 |
| Claudio Mattiussi | 2 | 739 | 36.42 |
| Jean-Christophe Zufferey | 3 | 467 | 46.55 |
| Dario Floreano | 4 | 3400 | 284.98 |