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Information Based Exploration with Panoramas and Angle Occupancy Grids

机译:与全景和角度占用网格的信息探索

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In this work we present a multi-robot information based exploration strategy with the goal of constructing high resolution 3D maps. We use a Cauchy-Schwarz Quadratic Mutual Information (CSQMI) based objective which operates on a novel angle enhanced occupancy grid to guide robots in the collection of RGBD panoramas, which have been shown to provide memory efficient high quality representations of space. To intelligently collect panoramas, we introduce the angle enhanced occupancy grid which emphasizes perspective in addition to coverage, a characteristic we believe results in the construction of higher quality maps than traditional occupancy grid methods. To show this, we conduct simulations and compare our approach with frontier exploration. Using our angle enhanced occupancy grid, only 11.4% of decimeter wall segments were covered by fewer than 20 pixels as compared with 33.5% for the frontier method.
机译:在这项工作中,我们提出了一种基于多机器人信息的探索策略,其目标是构建高分辨率3D地图。 我们使用基于CAUCHY-SCHWARZ二次相互信息(CSQMI)的目标,该目标在一个新的角度增强的占用电网上运行,以引导RGBD Panoramas的收集中的机器人,这已被证明可以提供记忆有效的空间高质量表示。 为了智能收集全景,我们介绍了角度增强的占用网格,除了覆盖范围之外,我们认为我们相信的特征在于建设高质量地图,而不是传统的占用网格方法。 为了表明这一点,我们进行仿真并与前沿探索进行比较。 使用我们的角度增强的占用电网,仅覆盖了11.4%的抽取壁段,较少于20像素,而前端方法的33.5%相比。

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