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arXiv · 1604.03526

Spatiotemporal Articulated Models for Dynamic SLAM

Suren Kumar·Vikas Dhiman·Madan Ravi Ganesh·Jason J. Corso
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Abstract

We propose an online spatiotemporal articulation model estimation framework that estimates both articulated structure as well as a temporal prediction model solely using passive observations. The resulting model can predict future mo- tions of an articulated object with high confidence because of the spatial and temporal structure. We demonstrate the effectiveness of the predictive model by incorporating it within a standard simultaneous localization and mapping (SLAM) pipeline for mapping and robot localization in previously unexplored dynamic environments. Our method is able to localize the robot and map a dynamic scene by explaining the observed motion in the world. We demonstrate the effectiveness of the proposed framework for both simulated and real-world dynamic environments.

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Suren Kumar, Vikas Dhiman, Madan Ravi Ganesh, Jason J. Corso. 2016-04-12. Spatiotemporal Articulated Models for Dynamic SLAM. https://arxiv.org/abs/1604.03526

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