A Framework for Realistic Simulation of Daily Human Activity
- URL: http://arxiv.org/abs/2311.15400v1
- Date: Sun, 26 Nov 2023 19:50:23 GMT
- Title: A Framework for Realistic Simulation of Daily Human Activity
- Authors: Ifrah Idrees, Siddharth Singh, Kerui Xu, Dylan F. Glas
- Abstract summary: This paper presents a framework for simulating daily human activity patterns in home environments at scale.
We introduce a method for specifying day-to-day variation in schedules and present a bidirectional constraint propagation algorithm for generating schedules from templates.
- Score: 1.8877825068318652
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: For social robots like Astro which interact with and adapt to the daily
movements of users within the home, realistic simulation of human activity is
needed for feature development and testing. This paper presents a framework for
simulating daily human activity patterns in home environments at scale,
supporting manual configurability of different personas or activity patterns,
variation of activity timings, and testing on multiple home layouts. We
introduce a method for specifying day-to-day variation in schedules and present
a bidirectional constraint propagation algorithm for generating schedules from
templates. We validate the expressive power of our framework through a use case
scenario analysis and demonstrate that our method can be used to generate data
closely resembling human behavior from three public datasets and a
self-collected dataset. Our contribution supports systematic testing of social
robot behaviors at scale, enables procedural generation of synthetic datasets
of human movement in different households, and can help minimize bias in
training data, leading to more robust and effective robots for home
environments.
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