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TAMAA: UPPAAL-based Mission Planning for Autonomous Agents


Publication Type:

Conference/Workshop Paper


The 35th ACM/SIGAPP Symposium On Applied Computing


Autonomous vehicles, such as construction machines, operate in hazardous environments while being required to function at high productivity. To meet both safety and productivity, planning obstacle-avoiding routes in an efficient and effective manner is of primary importance, especially when relying on autonomous vehicles to safely perform their missions. This work explores the use of model checking for the automatic generation of mission plans for autonomous vehicles, which are guaranteed to meet certain functional and extra-functional requirements (e.g., timing). We propose modeling of autonomous vehicles as agents in timed automata together with monitors for supervising their behavior in time (e.g., battery level). We automate this approach by implementing it in a tool called TAMAA (Timed-Automata-based Planner for Multiple Autonomous Agents) and integrating it with a mission-configuration tool. We demonstrate the applicability of our approach to an industrial autonomous wheel loader use case.


author = {Rong Gu and Eduard Paul Enoiu and Cristina Seceleanu},
title = {TAMAA: UPPAAL-based Mission Planning for Autonomous Agents},
month = {April},
year = {2020},
booktitle = {The 35th ACM/SIGAPP Symposium On Applied Computing},
url = {}