Online Horizon Selection in Receding Horizon Temporal Logic Planning
(2015) IEEE/RSJ International Conference on Intelligent Robots and Systems , 2015 p.3493-3499- Abstract
- Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of robotic applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the goal. We propose a receding horizon algorithm for reactive synthesis that automatically determines a path to the currently pursued goal at runtime, responding as needed to nondeterministic environment behavior. This is achieved by allowing each short horizon to have multiple local goals, and determining which local goal to pursue based on the current global goal, the currently perceived environment and a... (More)
- Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of robotic applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the goal. We propose a receding horizon algorithm for reactive synthesis that automatically determines a path to the currently pursued goal at runtime, responding as needed to nondeterministic environment behavior. This is achieved by allowing each short horizon to have multiple local goals, and determining which local goal to pursue based on the current global goal, the currently perceived environment and a pre-computed invariant dependent on the global goal. We demonstrate the utility of this additional flexibility in grant-response tasks, using a search-and-rescue example. Moreover, we show that these goal-dependent invariants mitigate the conservativeness of the receding horizon approach. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8167640
- author
- Raman, Vasumathi ; Fält, Mattias LU ; Wongpiromsarn, Tichakorn and Murray, Richard M.
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Formal Methods in Robotics and Automation, Reactive and Sensor-Based Planning, Task Planning
- host publication
- , 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- pages
- 7 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE/RSJ International Conference on Intelligent Robots and Systems , 2015
- conference location
- Hamburg, Germany
- conference dates
- 2015-09-28 - 2015-10-02
- external identifiers
-
- scopus:84958176294
- ISBN
- 978-1-4799-9994-1
- DOI
- 10.1109/IROS.2015.7353864
- language
- English
- LU publication?
- yes
- id
- 82159bcf-1a72-43eb-a376-bf58fc3942da (old id 8167640)
- date added to LUP
- 2016-04-04 13:34:22
- date last changed
- 2022-05-02 05:03:50
@inproceedings{82159bcf-1a72-43eb-a376-bf58fc3942da,
abstract = {{Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of robotic applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the goal. We propose a receding horizon algorithm for reactive synthesis that automatically determines a path to the currently pursued goal at runtime, responding as needed to nondeterministic environment behavior. This is achieved by allowing each short horizon to have multiple local goals, and determining which local goal to pursue based on the current global goal, the currently perceived environment and a pre-computed invariant dependent on the global goal. We demonstrate the utility of this additional flexibility in grant-response tasks, using a search-and-rescue example. Moreover, we show that these goal-dependent invariants mitigate the conservativeness of the receding horizon approach.}},
author = {{Raman, Vasumathi and Fält, Mattias and Wongpiromsarn, Tichakorn and Murray, Richard M.}},
booktitle = {{, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
isbn = {{978-1-4799-9994-1}},
keywords = {{Formal Methods in Robotics and Automation; Reactive and Sensor-Based Planning; Task Planning}},
language = {{eng}},
pages = {{3493--3499}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Online Horizon Selection in Receding Horizon Temporal Logic Planning}},
url = {{https://lup.lub.lu.se/search/files/11330608/8168710.pdf}},
doi = {{10.1109/IROS.2015.7353864}},
year = {{2015}},
}