Robust Self-Localization in Industrial Environments Based on 3D Ceiling Structures

Wulf, Oliver; Lecking, Daniel; Wagner, Bernd

doi:10.1109/iros.2006.282300

Cited by 17 publications

(11 citation statements)

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“…In [8] the AGV uses a 3D laser to detect the pallet, avoiding this way the problems associated with changes of illumination. In other works by the same authors, a laser scanner is also used for localization and generation of free-obstacles trajectories in factory buildings [25]. There are also some proposals that employ different sensory devices to provide better performance or even include the information of additional devices such as sonars [22].…”

Section: Related Workmentioning

confidence: 99%

Robust behavior and perception using hierarchical state machines: a pallet manipulation experiment

Peña¹,

Manso²,

Pinero³

et al. 2011

jopha

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Abstract-Interacting with simple objects in semi-controlled environments is a rich source of challenging situations for mobile robots, particularly when performing sequential tasks. In this paper we present the computational architecture and results obtained from a pallet manipulation experiment with a real robot. To achieve a good success rate in locating and picking the pallets a set of behaviors is assembled in a hierarchical state machine. The behaviors are arranged in such a way that the global uncertainty of the task is progressively reduced when approaching the goal. To do so, actions are generated in each stage that increase the confidence of the robot of being in that particular relation to the world. In order to set up this experiment, it is required a non-trivial set of working senso-motor behaviors. We build on this set to design and test a pallet moving task in which the robot has to locate, approach, obtain the pose, pick up and, finally move the pallet to its target position. The only sensory sources of information available to the robot are a binocular vision system and its internal odometry. To carry out this task we have equipped a RobEx robot with a 1 DOF forklift and a 4 DOF binocular head. We present the conceptual and computational models and the results of the experiments in a real setup.

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Section: Related Workmentioning

confidence: 99%

Robust behavior and perception using hierarchical state machines: a pallet manipulation experiment

Peña¹,

Manso²,

Pinero³

et al. 2011

jopha

View full text Add to dashboard Cite

show abstract

“…Localization and mapping approaches, based on 3D data acquired during movement, use either multiple 2D laser range finders facing different orientations, e.g., [17], or a single continuously rotating laser scanner [3], [20]. Alternatively, low cost 3D scanners can be built as pivot-mounted 2D laser scanners.…”

Section: Related Workmentioning

confidence: 99%

Robust 3D-mapping with time-of-flight cameras

May

Droeschel

Fuchs

et al. 2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

109

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Abstract-Time-of-Flight cameras constitute a smart and fast technology for 3D perception but lack in measurement precision and robustness. The authors present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are reduced by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.

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“…The resulting behavior of the robot is thus composed of stop-scan-move cycles. Wulf et al (2006) started using a continuously yawing scanner for acquiring 3D data while moving. They segment the data stream into individual point clouds and use the acquired information to localize the robot based on ceiling structures that are normally not occluded by people or objects.…”

Section: Continuously Rotating Laser Range Findersmentioning

confidence: 99%