Markerless Visual Control of a Quad-Rotor Micro Aerial Vehicle by Means of On-Board Stereo Processing

Schauwecker, Konstantin; Ke, Nan Rosemary; Scherer, Sebastian; Zell, Andreas

doi:10.1007/978-3-642-32217-4_2

Cited by 23 publications

(32 citation statements)

References 9 publications

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“…There exists, however, at least one example for sparse stereo matching with a forwardfacing camera pair [14]. Here, the sparsely matched features are used for a modified version of the SLAM method presented in [17], which itself is an extension of PTAM that incorporates depth information.…”

Section: Related Workmentioning

confidence: 99%

“…For the forward-facing cameras we use a method that largely matches the processing pipeline described in [14]. We improved the performance of this method mainly through code level optimizations and by resolving one problem in the original PTAM code, which in case of small maps causes Bundle Adjustment to be executed too frequently.…”

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

“…Those extensions will be explained later, when their necessity becomes apparent. For completeness, we provide a summary of the original method from [14] at this point.…”

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

“…Feature detection is, however, extended to include a scale space and an upper bound for the total number of features. We set our bound to 800 features, which is less than the 1000 features used in [14]. An example for the performance of this stereo method during indoor flight of our MAV is given in Fig.…”

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

“…Here, the IMU measurements are used for performing the Kalman prediction, while the Kalman correction is then executed with the estimated pose. Unlike in [14], we process the IMU measurements at a higher rate of 100 Hz.…”

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

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On-Board Dual-Stereo-Vision for the Navigation of an Autonomous MAV

Schauwecker

Zell

2013

J Intell Robot Syst

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We present a quadrotor Micro Aerial Vehicle (MAV) equipped with four cameras, which are arranged in two stereo configurations. The MAV is able to perform stereo matching for each camera pair on-board and in real-time, using an efficient sparse stereo method. In case of the camera pair that is facing forward, the stereo matching results are used for a reduced stereo SLAM system. The other camera pair, which is facing downwards, is used for ground plane detection and tracking. Hence, we are able to obtain a full 6DoF pose estimate from each camera pair, which we fuse with inertial measurements in an extended Kalman filter. Special care is taken to compensate various drift errors. In an evaluation we show that using two instead of one camera pair significantly increases the pose estimation accuracy and robustness.

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Section: Related Workmentioning

confidence: 99%

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

“…Those extensions will be explained later, when their necessity becomes apparent. For completeness, we provide a summary of the original method from [14] at this point.…”

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

Section: Processing Of Forward-facing Camerasmentioning

confidence: 99%

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