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Abstract
Mapping people dynamics is a crucial skill for robots, because it enables them to coexist in human-inhabited environments. However, learning a model of people dynamics is a time consuming process which requires observation of large amount of people moving in an environment. Moreover, approaches for mapping dynamics are unable to transfer the learned models across environments: each model is only able to describe the dynamics of the environment it has been built in. However, the impact of architectural geometry on people's movement can be used to anticipate their patterns of dynamics, and recent work has looked into learning maps of dynamics from occupancy. So far however, approaches based on trajectories and those based on geometry have not been combined. In this work we propose a novel Bayesian approach to learn people dynamics able to combine knowledge about the environment geometry with observations from human trajectories. An occupancy-based deep prior is used to build an initial transition model without requiring any observations of pedestrian; the model is then updated when observations become available using Bayesian inference. We demonstrate the ability of our model to increase data efficiency and to generalize across real large-scale environments, which is unprecedented for maps of dynamics.
Original language | English |
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Title of host publication | 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
Publisher | IEEE |
Pages | 12801-12807 |
Number of pages | 7 |
ISBN (Electronic) | 979-8-3503-7770-5 |
DOIs | |
Publication status | Published - 14 Oct 2024 |
MoE publication type | A4 Conference publication |
Event | IEEE/RSJ International Conference on Intelligent Robots and Systems - ADNEC, Abu Dhabi, United Arab Emirates Duration: 14 Oct 2024 → 18 Oct 2024 https://iros2024-abudhabi.org/ |
Publication series
Name | IEEE International Conference on Intelligent Robots and Systems |
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ISSN (Print) | 2153-0858 |
ISSN (Electronic) | 2153-0866 |
Conference
Conference | IEEE/RSJ International Conference on Intelligent Robots and Systems |
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Abbreviated title | IROS |
Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 14/10/2024 → 18/10/2024 |
Internet address |
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Dive into the research topics of 'Bayesian Floor Field: Transferring people flow predictions across environments'. Together they form a unique fingerprint.Projects
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Hypermaps: Hypermaps: closing the complexity gap in robotic mapping
Verdoja, F. (Principal investigator) & Nguyen, P. (Project Member)
01/09/2023 → 31/08/2027
Project: Academy of Finland: Other research funding