PDDL-Based Task Planning of Survey Missions for Autonomous Underwater Vehicles

PDDL-Based Task Planning of Survey Missions for Autonomous Underwater Vehicles: A generic planning system, taking into account location uncertainty and environmental properties

Steenstra, Lukas (TU Delft Mechanical, Maritime and Materials Engineering)

Sijs, Joris (mentor)
De Schutter, B.H.K. (graduation committee)
Yorke-Smith, N. (graduation committee)
Nunez, Alfredo (graduation committee)
Hommes, R.M. (graduation committee)

Delft University of Technology

Mechanical Engineering | Systems and Control

2019-09-23

Autonomous Underwater Vehicles (AUVs) are unmanned vehicles that give the opportunity to carry out lengthy and dangerous tasks autonomously. This is particularly useful for survey tasks, where the objective is to search the seafloor for objects. In this thesis work a planning system is developed that can plan a path for survey tasks, while considering environmental challenges such as communication limitations and location uncertainty. To compensate for location uncertainty, the planning system requires a higher level of abstraction compared to conventional path planning algorithms. For that reason, the planning problem is modelled in the PDDL, creating a powerful and flexible planning system which deals with the complex survey problem. Besides that, some additional planners are added to support the PDDL-planner and provide suitable plans for the AUV to carry out. The resulting plans are evaluated by simulation, showing that the planning system can successfully survey different scenarios. Besides that, the PDDL model is validated by means of the Event-B formal method, in order to obtain mathematical proofs of the validity of the planning model. The results are a step forward in achieving full autonomy of the AUVs. Besides that, a demonstration of the applicability of PDDL in real-world problems is given.

PDDL
task planning
survey task
AUV
Event-B

http://resolver.tudelft.nl/uuid:5bc6b1f4-1acf-4b40-8154-828427f9a4e9

Student theses

master thesis

© 2019 Lukas Steenstra