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Long-term exploration amp;amp; tours for energy constrained robots with online proprioceptive traversability estimation

机译:长期探索&能源受限机器人的旅游,具有在线预防性遍历遍历的估算

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This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles. We also present preliminary experimental results to show the feasibility of this approach in natural terrain.
机译:本文涉及本地化和能量受能限制的机器人通过采取最小化其能源消耗的路径和旅行,可以最大限度地提高现场的时间。机器人能量的重要组成部分消耗了移动性,并且是地形遍历的函数。我们从机器人移动的数据中估算在线的遍历,并使用它来生成地图,探索和最终会聚到环境的最小能量之旅。我们提供详细仿真和参数研究的结果,表明这种方法对机器人的效果,以具有未知的遍历的地形以及许多先验未知的硬障碍物。我们还提出了初步实验结果,以表明这种方法在天然地形中的可行性。

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