The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

We present an interactive perceptual skill for segmenting, tracking, and modeling the kinematic structure of 3D articulated objects. This skill is a prerequisite for general manipulation in unstructured environments. Robotenvironment interactions are used to move an unknown object, creating a perceptual signal that reveals the kinematic properties of the object. The resulting perceptual information can then inform and facilitate further manipulation. The algorithm is computationally efficient, handles partial occlusions, and depends on little object motion; it only requires sufficient texture for visual feature tracking. We conducted experiments with everyday objects on a robotic manipulation platform equipped with an RGB-D sensor. The results demonstrate the robustness of the proposed method to lighting conditions, object appearance, size, structure, and configuration.

Keywords

Interactive segmentation, kinematic modeling, manipulation

Notes

Sponsor: US Army Research Laboratory, Intel Science and Technology Center for Embedded Computing, DARPA Autonomous Robotic Manipulation Software Track (ARM-S)

Associated Center(s) / Consortia: National Robotics Engineering Center

Number of pages: 8

Text Reference

Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell, and Anthony (Tony) Stentz, "Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown 3D Articulated Objects," Proceedings of IEEE International Conference on Robotics and Automation, May, 2013.

BibTeX Reference

@inproceedings{Katz_2013_7406,
   author = "Dov Katz and Moslem Kazemi and J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz",
   title = "Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown 3D Articulated Objects",
   booktitle = "Proceedings of IEEE International Conference on Robotics and Automation",
   month = "May",
   year = "2013",
}

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