TY - GEN
T1 - Verifying Plans and Scripts for Robotics Tasks Using Performance Level Profiles
AU - Kovalchuk, Alexander
AU - Shekhar, Shashank
AU - Brafman, Ronen I.
N1 - Publisher Copyright: Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Performance-Level Profiles (PLPs) were introduced as a type of action representation language suitable for capturing the behavior of functional code for robotics. This paper considers two issues that PLPs raise: (1) Their formal semantics. (2) How to verify a script or plans that schedule the use of components that have been documented by PLPs. We discuss formal semantics for PLPs that maps them to probabilistic timed automata (PTAs). We also show how, given a script that refers to components specified using PLPs, we derive a PTA specification of the entire system. Using a model checker, we can now verify various properties of the system and answers queries about its behavior. Finally, we empirically evaluate an implemented system based on these ideas that use the UPPAAL-SMC model checker and demonstrate its scalability. The result is a pragmatic approach for verifying various properties of component-based robotic systems.
AB - Performance-Level Profiles (PLPs) were introduced as a type of action representation language suitable for capturing the behavior of functional code for robotics. This paper considers two issues that PLPs raise: (1) Their formal semantics. (2) How to verify a script or plans that schedule the use of components that have been documented by PLPs. We discuss formal semantics for PLPs that maps them to probabilistic timed automata (PTAs). We also show how, given a script that refers to components specified using PLPs, we derive a PTA specification of the entire system. Using a model checker, we can now verify various properties of the system and answers queries about its behavior. Finally, we empirically evaluate an implemented system based on these ideas that use the UPPAAL-SMC model checker and demonstrate its scalability. The result is a pragmatic approach for verifying various properties of component-based robotic systems.
UR - https://www.scopus.com/pages/publications/85124647499
U2 - 10.1609/icaps.v31i1.16016
DO - 10.1609/icaps.v31i1.16016
M3 - Conference contribution
T3 - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
SP - 673
EP - 681
BT - 31st International Conference on Automated Planning and Scheduling, ICAPS 2021
A2 - Biundo, Susanne
A2 - Do, Minh
A2 - Goldman, Robert
A2 - Katz, Michael
A2 - Yang, Qiang
A2 - Zhuo, Hankz Hankui
T2 - 31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Y2 - 2 August 2021 through 13 August 2021
ER -