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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 26 / No. 1: Twenty-Sixth AAAI Conference on Artificial Intelligence

Occupancy Grid Models for Robot Mapping in Changing Environments

March 8, 2023

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Authors

Daniel Meyer-Delius

KUKA Laboratories GmbH


Maximilian Beinhofer

University of Freiburg


Wolfram Burgard

University of Freiburg


DOI:

10.1609/aaai.v26i1.8377


Abstract:

The majority of existing approaches to mobile robot mapping assumes that the world is static, which is generally not justified in real-world applications. However, in many navigation tasks including trajectory planning, surveillance, and coverage, accurate maps are essential for the effective behavior of the robot.  In this paper we present a probabilistic grid-based approach for modeling changing environments. Our method represents both, the occupancy and its changes in the corresponding area where the dynamics are characterized by the state transition probabilities of a Hidden Markov Model. We apply an offline and an online technique to learn the parameters from observed data. The advantage of the online approach is that it can dynamically adapt the parameters and at the same time does not require storing the complete observation sequences.  Experimental results obtained with data acquired by real robots demonstrate that our model is well-suited for representing changing environments. Further results show that our technique can be used to substantially improve the effectiveness of path planning procedures.

Topics: AAAI

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HOW TO CITE:

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard Occupancy Grid Models for Robot Mapping in Changing Environments Proceedings of the AAAI Conference on Artificial Intelligence, 26 (2012) 2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard Occupancy Grid Models for Robot Mapping in Changing Environments AAAI 2012, 2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard (2012). Occupancy Grid Models for Robot Mapping in Changing Environments. Proceedings of the AAAI Conference on Artificial Intelligence, 26, 2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. Occupancy Grid Models for Robot Mapping in Changing Environments. Proceedings of the AAAI Conference on Artificial Intelligence, 26 2012 p.2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. 2012. Occupancy Grid Models for Robot Mapping in Changing Environments. "Proceedings of the AAAI Conference on Artificial Intelligence, 26". 2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. (2012) "Occupancy Grid Models for Robot Mapping in Changing Environments", Proceedings of the AAAI Conference on Artificial Intelligence, 26, p.2024

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard, "Occupancy Grid Models for Robot Mapping in Changing Environments", AAAI, p.2024, 2012.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. "Occupancy Grid Models for Robot Mapping in Changing Environments". Proceedings of the AAAI Conference on Artificial Intelligence, 26, 2012, p.2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. "Occupancy Grid Models for Robot Mapping in Changing Environments". Proceedings of the AAAI Conference on Artificial Intelligence, 26, (2012): 2024.

Daniel Meyer-Delius|| Maximilian Beinhofer|| Wolfram Burgard. Occupancy Grid Models for Robot Mapping in Changing Environments. AAAI[Internet]. 2012[cited 2023]; 2024.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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