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Agent-based approaches for exploration and pathfinding in unknown environments

机译：基于代理的探索和探索方法在未知环境中的探索方法

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This work evaluates and improves agent-based approaches for exploration of unknown terrain and finding (shortest) paths to a goal with an unknown location. This scenario is typically found in emergency incidents and for technically assisted search and rescue cases, e.g. when a building or a block of a city has been damaged by an earthquake and as a result, former maps are not valid anymore. In our approach we simulate the exploration of the unknown environment by agents that have different capabilities typically found in the technical assistance systems used in search and rescue operations, such as cameras, sensors, and limited communication abilities. The outcome of our simulation experiments indicates, which composition of a population of agents is best suited for efficient exploration of the unknown terrain, in terms of speed and path length. The results give hints which agent populations should be tried in a real world setting, in a search and rescue test scenario with real robots and sensors.
机译：这项工作评估并提高了基于代理的方法，以探索未知地形和寻找（最短）路径，以未知的位置。这种情况通常在紧急事件中找到以及技术辅助搜索和救援案件，例如，当建筑物或城市的街区因地震损坏时，前地图不再有效。在我们的方法中，我们通过在用于搜索和救援操作中使用的技术辅助系统中具有不同能力的代理商来模拟未知环境的探索，例如摄像机，传感器和有限的沟通能力。我们的模拟实验的结果表明，在速度和路径长度方面，该组合物的组成最适合于有效探索未知的地形。结果给出了在真正的世界环境中审判了代理人群的提示，以实际机器人和传感器在搜索和救援测试场景中进行了尝试。

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