Automatic unloading of heavy sacks from containers

Kirchheim, Alice; Burwinkel, M.; Echelmeyer, Wolfgang

doi:10.1109/ical.2008.4636286

Cited by 23 publications

(13 citation statements)

References 9 publications

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“…Some solutions have been developed, for instance, by Kirchheim et al [2], specifically for the grasping of coffee sacks. The gripper is supplied with four claw systems, with three concentric claws each.…”

Section: State Of the Art Of The Gripper Manufacturingmentioning

confidence: 99%

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Gripping Device for Heavy and Deformable Materials Handling: Concept, Design, Selection and Test

2014

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Automated handling of heavy deformable goods, due to their challenging material properties, sets a benchmark for handling sacks, such as bags of fabrics, synthetic packings, papers filled with coffee, cereals and plastic pellets. The paper focuses on the handling of jute coffee sacks.Nowadays the manipulation of jute coffee sacks is performed manually, because of the lack of specific grippers able to grasp this type of object. Hence, a set of concepts have been designed and developed to test the functionality of new devices, specifically intended to be used for the grasping of jute coffee sacks. Grippers have then been ranked through a Multiple Attribute Decision Making (MADM) method, in order to identify the best gripping tools for the handling of non-rigid materials. Finally, one of the most promising grippers has been designed and tested on real scale jute coffee sacks.

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Section: State Of the Art Of The Gripper Manufacturingmentioning

confidence: 99%

“…The unloading of these sacks from containers is done manually both in Third World countries and in industrialized nations. This operation implies high physical strain for workers, which causes problems like long-term physical diseases and frequent absences due to chronic illness [2].…”

Section: Introductionmentioning

confidence: 99%

Gripping Device for Heavy and Deformable Materials Handling: Concept, Design, Selection and Test

2014

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“…Therefore, the proposed segmentation procedure would not give correct results. Kirchheim et al use a standard point deviation which is characteristic for a sack surface filled with coffee beans [11]. Afterwards, this pattern is used for matching similar point deviations in the entire point cloud.…”

Section: Introductionmentioning

confidence: 99%

“…Certainly, the vision system can also be used for designing robotic systems in order to improve internal logistics processes within factories. Due to inconstant lightning conditions, existing approaches and systems typically use range data acquired by high accurate laser scanners [11] [17]. The range data can be represented as a point cloud expressed in xyzcoordinates in space as well as in range image format.…”

Section: Introductionmentioning

confidence: 99%

A 3D-robot vision system for automatic unloading of containers

Thamer

Kost

Weimer

et al. 2013

2013 IEEE 18th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

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Unloading of standard containers within logistic processes is mainly performed manually. Amongst gripping technology, the development of a robot vision system for recognizing different shaped logistic goods is a major technical obstacle for developing robotic systems for automatic unloading of containers. Goods can be arbitrarily placed inside a container and the resulting packaging scenarios usually have a high degree of occlusion. Existing systems and approaches use range information acquired by laser scanners for recognizing and localizing goods inside of containers. They are restricted to a single shape class of goods and often have limited size ranges for goods. This paper presents a robot vision for recognizing and localizing differently shaped and sized objects in piled packaging scenarios using range data acquired by different kinds of range sensors. After a specific segmentation step, different shaped partial surfaces are detected and classified in point cloud data and combined to complete logistic goods. The system is evaluated with real and simulated sensor data from different packaging scenarios.

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“…Recognizing and categorizing of different types of objects needs a model or a complete model database that contain a suitable description about the objects of interest. In today's logistic applications which use vision systems for categorizing goods, single and simple models for specific types of goods are used [1,2]. Therefore, these systems are not very flexible recognizing new objects or dealing with occlusions and local deformations of goods.…”

Section: Introductionmentioning

confidence: 99%

3D Object Categorization of Logistic Goods for Automated Handling

Thamer¹,

Weimer²,

Kost³

et al. 2013

Computer Graphics and Imaging / 798: Signal Processing, Pattern Recognition and Applications

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The automated handling of universal logistic goods through robotic systems requires suitable and reliable methods for categorizing different logistic goods. They must be able to detect the pose of different types and sizes of logistic goods in order to identify possible gripping points or for selecting a suitable gripping system for the detected object type. For this purpose, Time-of-Flight or Structured Light sensors can deliver a dense 3D representation of the investigated scenario. This paper presents a 3D object categorization system for logistic goods based on synthetically generated model data. We generate the model data by using a sensor simulation framework for different TOF-sensor types. The framework creates point clouds of self-defined geometric models of logistic goods or CAD data. Afterwards, we use these synthetic point clouds for generating a suitable model database offline. In order to evaluate our approach, we describe the synthetic point clouds by global point feature description techniques to distinguish between different types of logistic goods. Finally, we evaluate our concept with real sensor data from different logistic goods.

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Automatic unloading of heavy sacks from containers

Cited by 23 publications

References 9 publications

Gripping Device for Heavy and Deformable Materials Handling: Concept, Design, Selection and Test

Gripping Device for Heavy and Deformable Materials Handling: Concept, Design, Selection and Test

A 3D-robot vision system for automatic unloading of containers

3D Object Categorization of Logistic Goods for Automated Handling

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