@inbook{69f5d6cf6e494bf892388bb781827c40,
title = "Probabilistic Planning for Robotics with ROSPlan",
abstract = "Probabilistic planning is very useful for handling uncertainty in planning tasks to be carried out by robots. ROSPlan is a framework for task planning in the Robot Operating System (ROS), but until now it has not been possible to use probabilistic planners within the framework. This systems paper presents a standardized integration of probabilistic planners into ROSPlan that allows for reasoning with non-deterministic effects and is agnostic to the probabilistic planner used. We instantiate the framework in a system for the case of a mobile robot performing tasks indoors, where probabilistic plans are generated and executed by the PROST planner. We evaluate the effectiveness of the proposed approach in a real-world robotic scenario.",
author = "Gerard Canal and Michael Cashmore and Senka Krivi{\'c} and Guillem Aleny{\`a} and Daniele Magazzeni and Carme Torras",
year = "2019",
doi = "10.1007/978-3-030-23807-0_20",
language = "English",
isbn = "9783030238063",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "236--250",
editor = "Kaspar Althoefer and Jelizaveta Konstantinova and Ketao Zhang",
booktitle = "Towards Autonomous Robotic Systems - 20th Annual Conference, TAROS 2019, Proceedings",
address = "Germany",
note = "20th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2019 ; Conference date: 03-07-2019 Through 05-07-2019",
}