a specific physical context. In particular the kinematics of sailing vessels largely depend on the current wind, speed, etc. We use probabilistic roadmap planners to determine applicability of actions. The randomized approach to planning is particularly attractive for its ability to cover large search spaces. Furthermore, the approach can easily be integrated with a qualitative rule formalization. In this paper we demonstrate how the integration can be achieved. We also give first results of an integrated randomized-qualitative approach, demonstrating that reasonable control commands can be determined to control an autonomous robotic vessel in a rule-compliant manner.
In future work, we aim to reproduce our results in a sophisticated simulation context, stepping closer to control a real autonomous vessel. We plan to extend the qualitative rule formalization by high-level description of navigation recommendations to improve sailing performance (see Stelzer, Pr¨oll, and John (2007)). While we currently use a simple model to anticipate the actions of other agents, interesting scenarios like regatta racing call for a much more involved handling of multi-agent aspects. We are confident that the qualitative rule formalization provides excellent grounds to tackle such competitive multi-agent navigation problems.
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4 Towards Safe Navigation by Formalizing Naviagtion Rules
Arne Kreutzmann1, Diedrich Wolter1, Frank Dylla1, and Jae Hee Lee1 1 Cognitive Systems Group, University of Bremen, Bremen, Germany
Published in “TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation”, 2013, Volume 7, Number 2.
Contributions:
The study was conducted by Diedrich Wolter and me, resulting from my research on bridging the gap between a simple, verifiable spatial-logic and navigation concepts. Frank Dylla provided the necessary expertise in maritime sailing. Jae Hee Lee contributed his implementation of StarVars. I developed the tools and did most of the modeling. The manuscript was jointly prepared by all authors.
Acknowledgements:
This work is carried out in context of the Transregional Collaborative Research Center Spatial Cognition, project R3-[Q-Shape]. Financial support by the Deutsche Forschungsgemeinschaft (DFG) is gratefully acknowledged.
Abstract
One crucial aspect of safe navigation is to obey all navigation regulations applicable, in particular the collision regulations issued by the International Maritime Organization (IMO Colregs). Therefore, decision support systems for navigation need to respect Colregs and this feature should be verifiably correct. We tackle compliancy of navigation regulations from a perspective of software verification. One common approach is to use formal logic, but it requires to bridge a wide gap between navigation concepts and simple logic. We introduce a novel domain specification language based on a spatio-temporal logic that allows us to overcome this gap. We are able to capture complex navigation concepts in an easily comprehensible representation that can directly be utilized by various bridge systems and that allows for software verification.
4.1 Introduction
4.1 Introduction
Navigation regulations such as the official collision regulations of the International Maritime Organization (IMO Colregs) are an essential instrument for safety in navigation. Some situa-tions may require further rules and general recommendasitua-tions may be implemented to foster sensible navigation behavior, e.g., with respect to fuel effciency. All these regulations need to be obeyed-which can be a very demanding task in complex situations. By augmenting bridge systems such as ECDIS and autopilots to understand navigation regulations we can support crews, reducing the risk of regulation violations. To start with, this requires an implementation of navigation regulations that is known to be correct.
We argue for a declarative, logic-based approach to represent navigation regulations. Logics offer precise semantics for reasoning and they build a common basis for software verification.
The use of such formal methods during software development is a common requirement for higher standards of safety-critical software. However, logics are usually based on primitive concepts and it requires overly complex statements to represent everyday concepts such as
“oncoming traffic”. Trying to formalize a non-trivial set of navigation regulations with a simple logic inevitably leads to incomprehensible formalizations that are error-prone to align with navigation software, rendering effectiveness of the overall approach questionable.
The contribution of this paper is to show how the opposition of primitive concepts in logic on the one hand and abstract concepts in navigation regulations on the other hand can be overcome.
To this end, we develop an abstract logic, a so-called qualitative spatio-temporal logic, which can adequately represent navigation concepts. They allow comprehensible representations specifically suited for navigation problems. Qualitative spatial logics as studied in the field of Artificial Intelligence (AI) are acknowledged for their ability to grasp concepts of human cognition. We thus can connect formal logic to concepts of human cognition, obtaining formalizations with precise logic semantics that can be understood and even adapted by navigators, not only by computer science experts. These formalizations are universal in the sense that the very same representation can be used in a variety of tasks: to display regulation violations in ECDIS, to enforce rule-compliant path-planning in autopilots, and above all to support the software development process by verification.
This paper is organized as follows. We give references to related work, then we present our qualitative spatial logic. We outline how navigation formalizations in this logic can be integrated with various navigation tasks using logic-based software tools. Finally, we show how logic reasoning developed for our logic can be employed in verification and to reveal problems with software or with the regulations themselves. The paper concludes by a discussion and outlook section.