Paper Info
Title
An Anytime Algorithm for Chance Constrained Stochastic Shortest Path Problems and Its Application to Aircraft Routing
Abstract
Aircraft routing problem is a crucial component for flight automation. Despite recent successes, challenges still remain when the environment is dynamic and uncertain. In this paper, we tackle the following two challenges. First, when the environment is uncertain, it is much safer if the route planner can guarantee a specified level of safety. Second, when the environment is dynamic, the planner needs to adapt to the changes in the environment quickly. To address these challenges, we present three contributions. First, we propose formulating the aircraft routing problem under a dynamic and uncertain environment as a chance constrained stochastic shortest path (CC-SSP) problem. Second, we introduce an anytime algorithm for the CC-SSP problem, which is effective in a dynamic environment with limited planning time. To be more specific, we present two versions of the algorithm and compare their performances. Third, we show that the algorithm can be generalized to solve a larger class of problems called chance constrained partially observable Markov decision process (CC-POMDP).
Year
DOI
Venue
2021
10.1109/ICRA48506.2021.9561229
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
DocType
ISSN
Citations 
Conference
1050-4729
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Sungkweon Hong101.01
Sang Uk Lee21879180.39
X. Huang34421.44
Majid Khonji4359.10
Rashid Alyassi501.01
B C Williams62404426.13