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Risk-Aware Planning of Collaborative Mobile Robot Applications with Uncertain Task Durations
Publication Type:
Conference/Workshop Paper
Venue:
International Conference on Robot and Human Interactive Communication
Abstract
The efficiency of collaborative mobile robot applications is influenced by the inherent uncertainty introduced
by humans’ presence and active participation. This uncertainty
stems from the dynamic nature of the working environment,
various external factors, and human performance variability.
The observed makespan of an executed plan will deviate from
any deterministic estimate. This raises questions about whether
a calculated plan is optimal given uncertainties, potentially risking failure to complete the plan within the estimated timeframe.
This research addresses a collaborative task planning problem
for a mobile robot serving multiple humans through tasks such
as providing parts and fetching assemblies. To account for
uncertainties in the durations needed for a single robot and
multiple humans to perform different tasks, a probabilistic
modeling approach is employed, treating task durations as
random variables. The developed task planning algorithm
considers the modeled uncertainties while searching for the
most efficient plans. The outcome is a set of the best plans,
where no plan is better than the other in terms of stochastic
dominance. Our proposed methodology offers a systematic
framework for making informed decisions regarding selecting
a plan from this set, considering the desired risk level specific
to the given operational context.
Bibtex
@inproceedings{Lager6974,
author = {Anders Lager and Branko Miloradovic and Giacomo Spampinato and Thomas Nolte and Alessandro Papadopoulos},
title = {Risk-Aware Planning of Collaborative Mobile Robot Applications with Uncertain Task Durations},
month = {August},
year = {2024},
booktitle = {International Conference on Robot and Human Interactive Communication},
url = {http://www.es.mdu.se/publications/6974-}
}