TY - GEN
T1 - Optimal Multi-Valued LTL Planning for Systems with Access Right Levels
AU - Hekmatnejad, Mohammad
AU - Fainekos, Georgios
N1 - Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - We propose a method for optimal Linear Temporal Logic (LTL) planning under incomplete or uncertain knowledge with a minimum required truth degree. In order to introduce modeling flexibility to the framework, we propose semantics over ranges of truth values and operators that reason over such ranges of truth values. We show that the resulting optimal planning problem can be solved efficiently. In terms of application, we show how this method can be used for motion planning in autonomous driving cars for road networks with multiple degrees of accessibility.
AB - We propose a method for optimal Linear Temporal Logic (LTL) planning under incomplete or uncertain knowledge with a minimum required truth degree. In order to introduce modeling flexibility to the framework, we propose semantics over ranges of truth values and operators that reason over such ranges of truth values. We show that the resulting optimal planning problem can be solved efficiently. In terms of application, we show how this method can be used for motion planning in autonomous driving cars for road networks with multiple degrees of accessibility.
UR - http://www.scopus.com/inward/record.url?scp=85052578358&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052578358&partnerID=8YFLogxK
U2 - 10.23919/ACC.2018.8431556
DO - 10.23919/ACC.2018.8431556
M3 - Conference contribution
AN - SCOPUS:85052578358
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 2363
EP - 2370
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -