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Erschienen in:
Learning Transferable Policies for Monocular Reactive MAV Control Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

On the VINS Resource-Allocation Problem for a Dual-Camera, Small-Size Quadrotor

verfasst von : Kejian J. Wu, Tien Do, Luis C. Carrillo-Arce, Stergios I. Roumeliotis

Erschienen in: 2016 International Symposium on Experimental Robotics

Verlag: Springer International Publishing

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Abstract

In this paper, we present a novel resource-allocation problem formulation for vision-aided inertial navigation systems (VINS) for efficiently localizing micro aerial vehicles equipped with two cameras pointing at different directions. Specifically, based on the quadrotor’s current speed and median distances to the features, the proposed algorithm efficiently distributes processing resources between the two cameras by maximizing the expected information gain from their observations. Experiments confirm that our resource-allocation scheme outperforms alternative naive approaches in achieving significantly higher VINS positioning accuracy when tested onboard quadrotors with severely limited processing resources.

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Vorheriges Kapitel Localization of a Ground Robot by Aerial Robots for GPS-Deprived Control with Temporal Logic Constraints
Nächstes Kapitel Catching a Flying Ball with a Vision-Based Quadrotor
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Fußnoten
1
Although the two cameras’ fov have a small overlap, we do not match features between them as the different camera characteristics make such process unreliable.
 
2
Note that although the ensuing presentation focuses on the specific (forward and downward) configuration of the cameras onboard the Bebop quadrotor used in our experiments, our approach is applicable to any dual-camera system with arbitrary geometric configuration.
 
3
Without loss of generality, we choose the quadrotor’s frame of reference to be the one of the downward camera.
 
4
Through experimentation, [9] has been shown to offer a very efficient and accurate metric for assessing the expected information gain from each feature.
 
5
MSCKF features are marginalized by the SR-ISWF for performing visual-inertial odometry without including their estimates in the filter’s state; see [17] for details.
 
6
We do not evaluate the RMSE for the case of only downward-pointing camera since the quadrotor’s CPU cannot perform image processing at the high frame rates (40 Hz) required for tracking features at high speeds (6 m/s).
 
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Grabe, V., Bülthoff, H.H., Scaramuzza, D., Giordano, P.R.: Nonlinear ego-motion estimation from optical flow for online control of a quadrotor UAV. Int. J. Robot. Res. 34(8), 1114–1135 (2015)CrossRef
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Kottas, D.G., DuToit, R.C., Ahmed, A., Guo, C.X., Georgiou, G., Li, R., Roumeliotis, S.I.: A resource-aware vision-aided inertial navigation system for wearable and portable computers. In: Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China, pp. 6336–6343, 31 May– 5 June 2014
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Pless, R.: Using many cameras as one. In: Proceeding of the IEEE International Conference on Computer Vision and Pattern Recognition, Madison, WI, pp. 11–18, 16–22 June 2003
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Rosten, E., Drummond, T.: Machine learning for high-speed corner detection. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 430–443. Springer, Heidelberg (2006). doi:10.​1007/​11744023_​34 CrossRef
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Schauwecker, K., Zell, A.: On-board dual-stereo-vision for the navigation of an autonomous MAV. J. Intell. Robot. Syst. 74(1–2), 1–16 (2014)CrossRef
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Shen, S., Mulgaonkar, Y., Michael, N., Kumar, V.: Vision-based state estimation and trajectory control towards high-speed flight with a quadrotor. In: Proceedings of the Robotics: Science and Systems, Berlin, Germany, 24–28 June 2013
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Weiss, S., Achtelik, M.W., Lynen, S., Achtelik, M.C., Kneip, L., Chli, M., Siegwart, R.: Monocular vision for long-term micro aerial vehicle state estimation: a compendium. J. Field Robot. 30(5), 803–831 (2013)CrossRef
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Wu, K.J., Ahmed, A., Georgiou, G., Roumeliotis, S.I.: A square root inverse filter for efficient vision-aided inertial navigation on mobile devices. In: Proceedings of Robotics: Science and Systems, Rome, Italy, 13–17 July 2015
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Metadaten
Titel
On the VINS Resource-Allocation Problem for a Dual-Camera, Small-Size Quadrotor
verfasst von
Kejian J. Wu
Tien Do
Luis C. Carrillo-Arce
Stergios I. Roumeliotis
Copyright-Jahr
2017
Buch
2016 International Symposium on Experimental Robotics

Print ISBN: 978-3-319-50114-7

Electronic ISBN: 978-3-319-50115-4

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-50115-4_47

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