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For some complex queries it would be helpful to address all knowledge gathered during observations, in particular information about goods we have observed before and which are included in the map, but which we are unable to perceive at the very moment. Currently, we take an conservative approach that only explicates knowledge that is certain. However, for such objects we still have a strongbelief of their existence and position in the warehouse , but this belief can—according to the actual observation—not be validated. A possibility to include reasoning on such beliefs is to use a logic that provides a modal belief operator, such as the logic for BDI agents presented in (Meyer and Veltman, 2007). Another source of information for more complex queries could be provided by an ontology, as shown in (Mastrogiovanni, Sgorbissa, and Zaccaria, 2009).
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3 Rule-Compliant Navigation With Qualitative Spatial Reasoning
Diedrich Wolter1, Frank Dylla1andArne Kreutzmann1
1 Cognitive Systems Group, University of Bremen, Bremen, Germany
Published in “Proceedings of the 4th International Robotic Sailing Conference”, 2011, Springer.
Contributions:
This paper resulted from intense discussions between the three authors, about how to best integrate my approach with possible control of a robotic sailboat. I introduced the idea of using a random roadmap planner. The study as well as the manuscript preparation was conducted by Diedrich Wolter. The modeling was based on Frank Dylla’s work and he kindly provided it.
Acknowledgements:
This work is supported by the Deutsche Forschungsgemeinschaft (DFG) in context of the transregional collaborative research center SFB/TR 8Spatial Cognition, project R3-[Q-Shape].
Financial support is gratefully acknowledged. We also acknowledge the comments of the anonymous reviewers.
Abstract
We develop a formal, symbolic representation of right-of-way-rules for sea navigation based on a qualitative spatial representation. Navigation rules specified qualitatively allow an autonomous agent consistently to combine all rules applicable in a context. The focus of this paper is to show how the abstract rule specification can be used during path-planning. We propose a randomized-qualitative approach to navigation, integrating the symbolic level with a probabilistic roadmap planner. The resulting navigation system maneuvers under the side constraint of rule compliancy.
Evaluating our approach with case studies we demonstrate that qualitative navigation rules contributes to autonomous sailing.
3.1 Introduction
3.1 Introduction
A considerable amount of everyday behavior is not self-determined but subject to regulations.
For example, right-of-way regulations govern how to travel public spaces. Action planning for an autonomous agent needs to respect right-of-way regulations. These rules are special in that they have been designed for the general public and are denoted in natural language, using abstract concepts of space. Making these regulations accessible to an artificial agent requires translating them into a formal language that can be understood by the agent and which seamlessly integrates with the agent’s navigation process. In order to facilitate correctness and verifiability of the translation, an abstract language is particularly suited if it is able to reflect the concepts originally used in the right-of-way regulations. We usequalitative representations to abstract real-wold observations to abstract knowledge about space and time on a conceptual level. Qualitative spatial representations (see Cohn and Renz (2007) for an overview) aim to provide a formal model for human-level commonsense understanding of space and time.
Moreover, they enable abstract reasoning processes. Technically, qualitative representations summarize similar real-world states by a discrete, finite set of qualitative categories that give rise to symbolic reasoning.
This paper demonstrates the utility of qualitative reasoning in autonomous sea navigation. In previous work we have studied how purely symbolic reasoning can help to consistently integrate pair-wise rule constraints when multiple agents meet (Dylla et al., 2007). We now focus on the problem of actually controlling a vessel in a rule-compliant manner. The contribution of our work is to show how the official right-of-way rules for vessel navigation (COLREGS: vessels in sight of each other) according to the International Maritime Organization (IMO) can be modeled using qualitative spatial representation. Furthermore, we show how the representation supports rule-compliant action planning for autonomous vessels. This paper is organized as follows. We start by putting our approach in the context of high-level agent control. Section 3.3 introduces qualitative representation and reasoning techniques. Using these techniques, Section 3.4 details our formalization of navigation rules. Section 3.5 explains how we incorporate the qualitative rules into action planning. We give an experimental account of our approach in Section 3.6 and conclude the paper by summarizing the results and discussing further research directions.