Container Localisation and Mass Estimation with an RGB-D Camera
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866909605074829312 |
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| author | Apicella, Tommaso Slavic, Giulia Ragusa, Edoardo Gastaldo, Paolo Marcenaro, Lucio |
| author_facet | Apicella, Tommaso Slavic, Giulia Ragusa, Edoardo Gastaldo, Paolo Marcenaro, Lucio |
| contents | In the research area of human-robot interactions, the automatic estimation of the mass of a container manipulated by a person leveraging only visual information is a challenging task. The main challenges consist of occlusions, different filling materials and lighting conditions. The mass of an object constitutes key information for the robot to correctly regulate the force required to grasp the container. We propose a single RGB-D camera-based method to locate a manipulated container and estimate its empty mass i.e., independently of the presence of the content. The method first automatically selects a number of candidate containers based on the distance with the fixed frontal view, then averages the mass predictions of a lightweight model to provide the final estimation. Results on the CORSMAL Containers Manipulation dataset show that the proposed method estimates empty container mass obtaining a score of 71.08% under different lighting or filling conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_01207 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Container Localisation and Mass Estimation with an RGB-D Camera Apicella, Tommaso Slavic, Giulia Ragusa, Edoardo Gastaldo, Paolo Marcenaro, Lucio Computer Vision and Pattern Recognition Robotics Image and Video Processing In the research area of human-robot interactions, the automatic estimation of the mass of a container manipulated by a person leveraging only visual information is a challenging task. The main challenges consist of occlusions, different filling materials and lighting conditions. The mass of an object constitutes key information for the robot to correctly regulate the force required to grasp the container. We propose a single RGB-D camera-based method to locate a manipulated container and estimate its empty mass i.e., independently of the presence of the content. The method first automatically selects a number of candidate containers based on the distance with the fixed frontal view, then averages the mass predictions of a lightweight model to provide the final estimation. Results on the CORSMAL Containers Manipulation dataset show that the proposed method estimates empty container mass obtaining a score of 71.08% under different lighting or filling conditions. |
| title | Container Localisation and Mass Estimation with an RGB-D Camera |
| topic | Computer Vision and Pattern Recognition Robotics Image and Video Processing |
| url | https://arxiv.org/abs/2203.01207 |