Abstract
Quantiles of a natural phenomena can provide scientists with an important understanding of typical, extreme, or other spreads of concentrations. When a group has several available robots, or teams of scientists come together to study a particular environment, it may be advantageous to pool robot resources in a collaborative way to improve performance. A multirobot team can be difficult to practically bring together and coordinate, especially when robot communication is involved. To this end, we present a study across several axes of the impact of using multiple robots to estimate quantiles of a distribution of interest using an informative path planning formulation. We measure quantile estimation accuracy with increasing team size to understand what benefits result from a multirobot approach in a drone exploration task of analyzing the algae concentration in lakes. We additionally perform an analysis on several parameters, including the spread of robot initial positions, the planning budget, and inter-robot communication, and find that while using more robots generally results in lower estimation error, this benefit is achieved under certain conditions. We present our findings in the context of real field robotic applications and discuss the implications of the results and interesting directions for future work.
Abstract (translated)
自然事物的Quantile可以提供科学家对典型、极端或其他聚集分布的重要理解。当一个团队有多个可用机器人,或一群科学家聚集研究特定的环境时,采用合作的方式整合机器人资源可以提高性能可能是有益的。多机器人团队在实践中很难实际地组织并协调,特别是在涉及机器人通信的情况下。因此,我们提出了一项跨越多个轴的研究,探讨使用多个机器人使用 informative 路径规划框架估计感兴趣的分布quantiles的影响。我们随着团队规模的增加测量Quantile估计的准确性,以了解在无人机探索任务中,多机器人方法如何带来好处,特别是在涉及机器人通信的情况下。我们还对多个参数进行了分析,包括机器人初始位置的分布、规划预算和机器人之间的通信,并发现,虽然使用更多的机器人通常会导致更低的估计误差,但在特定条件下,可以实现这种好处。我们在实际 field robotic 应用的背景下介绍了我们的研究结果,并讨论了结果及其对未来的工作的有意义的方向。
URL
https://arxiv.org/abs/2303.03539
