Biomechatronics Group, Faculty of Engineering and Mathematics, University of Applied Sciences, Bielefeld, Germany. Active Sensing, Faculty of Biology, Bielefeld University, Bielefeld, Germany.
Bioinspir Biomim. 2018 Oct 16;13(6):066008. doi: 10.1088/1748-3190/aae23f.
In addition to their visual sense, weakly electric fish use active electrolocation to detect and analyse objects in their nearby environment. Their ability to generate and sense electric fields combined with scanning-like swimming movements are intended to extract further parameters like the size, shape and material properties of objects. Inspired by this biological example, this work introduces an application for active electrolocation based on reduced sensor movement sequences as presented in Wolf-Homeyer et al (2016 Bioinspir. Biomim. 11 055002). Initially, the application is conducted with a simulated receptor-system consisting of an emitter-dipole and an orthogonally arranged pair of sensor-electrodes. Close inspection of a minimal set of scanning movements allows the exclusion of sectors of the general search area early in the proposed localization algorithm (search area partitioning). Furthermore, the proposed algorithm is based on an analytical representation of the electric field and of the so-called EEV (ensemble of electrosensory viewpoints) (Solberg et al 2008 Int. J. Robot. Res. 27 529-48) rather than using computationally expensive FEM simulations, rendering it suitable for embedded computer systems. Two-dimensional discrete EEV contour-ring points (CRPs) of desired accuracy are extracted. In the core of the localization algorithm, fragments of the EEV are selected from valid sectors of the search area, which generates sets of CRPs, one for each sensor-emitter position/orientation. These sets are investigated by means of a nearness metric to find points in different sets which correspond to each other in order to estimate the object position. Two resultant scanning strategies/localization algorithms are introduced.
除了视觉感知外，弱电鱼还利用主动电定位来探测和分析周围环境中的物体。它们产生和感测电场的能力与扫描式游动相结合，旨在提取物体的进一步参数，如大小、形状和材料特性。受这一生物实例的启发，这项工作介绍了一种基于 Wolf-Homeyer 等人（2016 年《生物灵感与仿生学》11 号 055002）提出的减少传感器运动序列的主动电定位应用。最初，该应用程序是使用由发射器偶极子和正交排列的一对传感器电极组成的模拟接收系统进行的。通过仔细检查最小的扫描运动集合，可以在提出的定位算法（搜索区域分区）中尽早排除一般搜索区域的扇区。此外，所提出的算法基于电场的解析表示和所谓的 EEV（集合的电感觉视点）（Solberg 等人，2008 年《国际机器人研究杂志》27 529-48），而不是使用计算成本高昂的有限元模拟，使其适合嵌入式计算机系统。提取所需精度的二维离散 EEV 轮廓环点（CRP）。在定位算法的核心部分，从搜索区域的有效扇区中选择 EEV 的片段，这些片段为每个传感器发射器位置/方向生成一组 CRP。通过接近度量来研究这些集合，以找到不同集合中彼此对应的点，从而估计物体的位置。引入了两种结果扫描策略/定位算法。
