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Towards a model of UAVs navigation in urban canyon through defeasible logic

机译：通过可行逻辑建立无人机在城市峡谷中的航行模型

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This article shows how a non-monotonic rule based system (defeasible logic) can be integrated with numerical computation engines, and how this can be applied to solve the Vehicle Routing Problem. To this end, we have simulated a physical system from which we can obtain numerical information. The physical system perceives information from its environment and generates predicates that can be reasoned by a defeasible logic engine. The conclusions/decisions derived will then be realized by the physical system as it takes actions based on the conclusion derived. Here we consider a scenario where a 'flock' of Unmanned Autonomous Vehicles (UAVs) have to navigate within an urban canyon environment. The UAVs are self-autonomous without centralized control. The goal of the UAVs is to navigate to their desired destinations without colliding with each other. In case of possible collision, the UAVs concerned will communicate with each other and use their background knowledge or travel guidelines to resolve the conflicts.
机译：本文说明了如何将基于非单调规则的系统（可行逻辑）与数值计算引擎集成在一起，以及如何将其应用于解决车辆路径问题。为此，我们模拟了一个物理系统，可以从中获得数值信息。物理系统从其环境中感知信息，并生成可被不可行的逻辑引擎推理的谓词。然后，当物理系统基于所得出的结论采取行动时，所得出的结论/决定将由物理系统实现。在这里，我们考虑无人驾驶自动驾驶汽车（UAV）的“群”必须在城市峡谷环境中航行的场景。无人机是自动自治的，无需集中控制。无人机的目标是导航到其所需的目的地而不会彼此碰撞。如果可能发生碰撞，相关的无人机将相互通信，并使用其背景知识或旅行指南来解决冲突。

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