Fusing Joint Measurements and Visual Features for In-Hand Object Pose Estimation
| Autor: | Martin Pfanne, Alin Albu-Schaffer, Freek Stulp, Maxime Chalon |
|---|---|
| Přispěvatelé: | Bicchi, Antonie, Ding, Han |
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Biomedical Engineering 02 engineering and technology Kinematics Extended Kalman filter 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Computer vision Pose Perception for grasping and manipulation sensor fusion business.industry Mechanical Engineering 020208 electrical & electronic engineering GRASP Object (computer science) Computer Science Applications Visualization Human-Computer Interaction Control and Systems Engineering Kognitive Robotik Robot dexterous manipulation Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | IEEE Robotics and Automation Letters. 3:3497-3504 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2018.2853652 |
| Popis: | For a robot to perform complex manipulation tasks, such as an in-hand manipulation, knowledge about the state of the grasp is required at all times. Moreover, even simple pick-and-place tasks may fail because unexpected motions of the object during the grasp are not accounted for. This letter proposes an approach that estimates the grasp state by combining finger measurements, i.e., joint positions and torques, with visual features that are extracted from monocular camera images. The different sensor modalities are fused using an extended Kalman filter. While the finger measurements allow to detect contacts and resolve collisions between the fingers and the estimated object, the visual features are used to align the object with the camera view. Experiments with the DLR robot David demonstrate the wide range of objects and manipulation scenarios that the method can be applied to. They also provide an insight into the strengths and limitations of the different complementary types of measurements. |
| Databáze: | OpenAIRE |
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