Object Recognition for Robotics Based on Planar Reconstructed B-Rep Models

Rohner, Dorian; Henrich, Dominik

doi:10.1109/irc.2019.00027

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…The SIFT keypoints are used to determine correspondences and with the underlying 3D information the 6 DOF transformation from the model to the point cloud is calculated. On the other hand, we apply a surfaced based object recognition method [3] based on boundary representation models (BReps). Our new model is transformed into a BRep by utilizing [13] and added to the object database.…”

Section: Validationmentioning

confidence: 99%

“…Our new model is transformed into a BRep by utilizing [13] and added to the object database. Then we capture a scene as a BRep [13] with a Kuka LWR 4 and an Ensenso N10 and use the method from [3] for object recognition. In Fig.…”

Section: Validationmentioning

confidence: 99%

“…Therefore, it is necessary for the robot to recognize its environment. Several object recognition methods use an object database, which stores models for all potential workpieces [1][2][3]. Depending on the underlying recognition method, different types of models are stored, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Robot-Based Creation of Complete 3D Workpiece Models

Rohner

Henrich

2022

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021

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A complete object database containing a model (representing geometric and texture information) of every possible workpiece is a common necessity e.g. for different object recognition or task planning approaches. The generation of these models is often a tedious process. In this paper we present a fully automated approach to tackle this problem by generating complete workpiece models using a robotic manipulator. A workpiece is recorded by a depth sensor from multiple views for one side, then turned, and captured from the other side. The resulting point clouds are merged into one complete model. Additionally, we represent the information provided by the object’s texture using keypoints. We present a proof of concept and evaluate the precision of the final models. In the end we conclude the usefulness of our approach showing a precision of around 1 mm for the resulting models.

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Section: Validationmentioning

confidence: 99%

Section: Validationmentioning

confidence: 99%

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Robot-Based Creation of Complete 3D Workpiece Models

Rohner

Henrich

2022

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2021

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Detection and Handling of Dynamic Scenes During an Active Vision Process for Object Recognition Using a Boundary Representation

Rohner¹,

Hartwig²,

Henrich³

2023

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2022

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For robot manipulators, it is nowadays necessary to know their surroundings. This knowledge consists at least of a world representation with recognized objects. During the reconstruction of scene objects from multiple views, changes, like positioning of the objects, or additional unwanted signals, like parts of a human co-worker, may occur. In this paper, we classify the possible changes for a specific type of representation (boundary representation models). Afterwards, we present an approach to detect and handle these changes to maintain a valid world model. To achieve this, we compare what should be visible in the world model reconstructed thus far with the actual information from the current view. The detected change is handled by using object hypotheses as well as geometric information from the world representation. Based on an evaluation, we show a proof of concept and the usefulness of our approach and suggest future work.

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Using Active Vision for Enhancing an Surface-based Object Recognition Approach

Rohner

Henrich

2020

2020 Fourth IEEE International Conference on Robotic Computing (IRC)

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Object Recognition for Robotics Based on Planar Reconstructed B-Rep Models

Cited by 3 publications

References 15 publications

Robot-Based Creation of Complete 3D Workpiece Models

Robot-Based Creation of Complete 3D Workpiece Models

Detection and Handling of Dynamic Scenes During an Active Vision Process for Object Recognition Using a Boundary Representation

Using Active Vision for Enhancing an Surface-based Object Recognition Approach

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