Integration of 6D Object Localization and Obstacle Detection for Collision Free Robotic Manipulation

Grundmann, Thilo; Eidenberger, Robert; Zoellner, Raoul; Xue, Zhixing; Ruehl, Steffen W.; Zoellner, J. Marius; Dillmann, Ruediger; Kuehnle, J. U.; Verl, Alexander

doi:10.1109/si.2008.4770428

Cited by 13 publications

(9 citation statements)

References 11 publications

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“…Traditionally the extrinsic calibration has been addressed by considering the intensity image of the ToF camera and using classical stereo calibration algorithms [56], [62]- [64]. Unfortunately, due to the low resolution of the sensor, this approach suffers from the same problems as the ones presented for intrinsic calibration.…”

Section: B Extrinsicmentioning

confidence: 99%

Lock-in Time-of-Flight (ToF) Cameras: A Survey

2011

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Abstract-This paper reviews the state-of-the art in the field of lock-in ToF cameras, their advantages, their limitations, the existing calibration methods, and the way they are being used, sometimes in combination with other sensors. Even though lockin ToF cameras provide neither higher resolution nor larger ambiguity-free range compared to other range map estimation systems, advantages such as registered depth and intensity data at a high frame rate, compact design, low weight and reduced power consumption have motivated their increasing usage in several research areas, such as computer graphics, machine vision and robotics.

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Section: B Extrinsicmentioning

confidence: 99%

Lock-in Time-of-Flight (ToF) Cameras: A Survey

2011

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“…A classical solution in the area of object modeling is the use of calibrated stereo rigs. Therefore, initial works were devoted to their comparison with [37] Dynamic object detection and classification Color and light independence PMD Hussmann and Liepert [38] Object pose Easy object/background segmentation PMD Guomundsson et al [39] Known object pose estimation Light independent / Absolute scale SR3 Beder et al [40] Surface reconstruction using patchlets ToF easily combines with stereo PMD Fuchs and May [7] Precise surface reconstruction 3D at high rate SR3/O3D100 (Depth) Dellen et al [5] 3D object reconstruction 3D at high rate SR3 (Depth) Foix et al [6] Kuehnle et al [8] Object recognition for grasping 3D allow geometric primitives search SR3 Grundmann et al [41] Collision free object manipulation 3D at high rate SR3 + stereo Reiser and Kubacki [42] Position based visual servoing 3D is simply obtained / No model needed SR3 (Depth) Gachter et al [43] Object part detection for classification 3D at high rate SR3 Shin et al [44] SR2 Klank et al [45] Mobile manipulation Easy table/object segmentation SR4 Marton et al [46] Object categorization ToF easily combines with stereo SR4 + color Nakamura et al [47] Mobile manipulation Easy table segmentation SR4 + color Saxena et al [9] Grasping unknown objects 3D at high rate SR3 + stereo Zhu et al [48] Short range depth maps ToF easily combines with stereo SR3 + stereo Lindner et al [49] Object segmentation for recognition Easy color registration PMD + color camera Fischer et al [50] Occlusion handling in virtual objects 3D at high rate PMD + color camera…”

Section: Object-related Tasksmentioning

confidence: 99%

“…Although they use depth images rectified up to some level, their system is not reliable enough. In a subsequent work [41] they use the ToF camera to detect unknown objects and classify them as obstacles, and use a stereo camera system to identify known objects using SIFT features. As it is widely known, this second approach requires textured objects while their first approach does not.…”

Section: Object-related Tasksmentioning

confidence: 99%

ToF cameras for active vision in robotics

Alenyà

Foix

Torras

2014

Sensors and Actuators A: Physical

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ToF cameras are now a mature technology that is widely being adopted to provide sensory input to robotic applications. Depending on the nature of the objects to be perceived and the viewing distance, we distinguish two groups of applications: those requiring to capture the whole scene and those centered on an object. It will be demonstrated that it is in this last group of applications, in which the robot has to locate and possibly manipulate an object, where the distinctive characteristics of ToF cameras can be better exploited.After presenting the physical sensor features and the calibration requirements of such cameras, we review some representative works highlighting for each one which of the distinctive ToF characteristics have been more essential. Even if at low resolution, the acquisition of 3D images at frame-rate is one of the most important features, as it enables quick background/foreground segmentation. A common use is in combination with classical color cameras. We present three developed applications, using a mobile robot and a robotic arm, to exemplify with real images some of the stated advantages.

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“…The mean values of the measurement distribution are determined from the stereo matching algorithm on the basis of feature correspondences [14]. The uncertainties result from relations between seen and expected interest points, matching errors and sensor and feature characteristics.…”

Section: B Uncertainties In the Observation Modelmentioning

confidence: 99%

Probabilistic occlusion estimation in cluttered environments for active perception planning

Eidenberger

Zoellner

Scharinger

2009

2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Abstract-This paper presents a probabilistic framework for scene modeling and active perception planning in complex environments. It tackles the problems of representing detection and transition uncertainties in multi-object scenes without knowledge of the total number of objects in the scenario. The correct association of observation data with scene information is essential for reasonable incorporation of sequencing measurements into the scene model. This work also deals with the probabilistic computation of object occlusions for probabilistic action planning in order to select the most profitable prospective viewpoint. Concepts from computer graphics and statistics are combined for the efficient and precise estimation of future observations.In an experimental setting this active perception system, integrated into an autonomous service robot, is evaluated in a kitchen scenario.

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Integration of 6D Object Localization and Obstacle Detection for Collision Free Robotic Manipulation

Cited by 13 publications

References 11 publications

Lock-in Time-of-Flight (ToF) Cameras: A Survey

Lock-in Time-of-Flight (ToF) Cameras: A Survey

ToF cameras for active vision in robotics

Probabilistic occlusion estimation in cluttered environments for active perception planning

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