Lightbody, Peter, Baxter, Paul and Hanheide, Marc (2018) Studying table-top manipulation tasks: a robust framework for object tracking in collaboration. In: The 13th Annual ACM/IEEE International Conference on Human Robot Interaction, 5 - 8 March 2018, Chicago, IL, USA.
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HRI_lbr_18.pdf - Whole Document 591kB |
Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
Abstract
Table-top object manipulation is a well-established test bed on which to study both basic foundations of general human-robot interaction and more specific collaborative tasks. A prerequisite, both for studies and for actual collaborative or assistive tasks, is the robust perception of any objects involved. This paper presents a real-time capable and ROS-integrated approach, bringing together state-of-the-art detection and tracking algorithms, integrating perceptual cues from multiple cameras and solving detection, sensor fusion and tracking in one framework. The highly scalable framework was tested in a HRI use-case scenario with 25 objects being reliably tracked under significant temporary occlusions. The use-case demonstrates the suitability of the approach when working with multiple objects in small table-top environments and highlights the versatility and range of analysis available with this framework.
Keywords: | Fiducial Markers, Visual Tracking, Human Robot Collaboration, bmjdoi |
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Subjects: | G Mathematical and Computer Sciences > G440 Human-computer Interaction G Mathematical and Computer Sciences > G740 Computer Vision G Mathematical and Computer Sciences > G400 Computer Science |
Divisions: | College of Science |
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ID Code: | 31204 |
Deposited On: | 07 Mar 2018 13:40 |
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