Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, United States of America.
Civil, Environmental, and Architectural Engineering, University of Colorado Boulder, Boulder, CO 80309, United States of America.
J Theor Biol. 2024 Dec 7;595:111941. doi: 10.1016/j.jtbi.2024.111941. Epub 2024 Sep 11.
Two simple algorithms based on combining odor concentration differences across time and space along with information on the flow direction are tested for their ability to locate an odor source in four different odor landscapes. Image data taken from air plumes in three different regimes and a water plume are used as test environments for a bilateral ("stereo sampling") algorithm using concentration differences across two sensors and a "casting" algorithm that uses successive samples to decide orientation. Agents are started at random locations and orientations in the landscape and allowed to move until they reach the source of the odor (success) or leave the imaged area (failure). Parameters for the algorithm are chosen to optimize success and to minimize path length to the source. Success rates over 90% are consistently obtained with path lengths that can be as low as twice the starting distance from the source in air and four times the distance in the highly turbulent water plumes. We find that parameters that optimize success often lead to more exploratory pathways to the source. Information about the direction from which the odor is coming is necessary for successful navigation in the water plume and reduces the path length in the three tested air plumes.
我们测试了两种基于时间和空间的气味浓度差异结合以及流向信息的简单算法,以评估它们在四种不同气味环境中定位气味源的能力。我们使用来自三种不同状态的空气羽流和水羽流的图像数据作为测试环境,测试了一种使用两个传感器之间的浓度差异的双边(“立体采样”)算法和一种使用连续样本来确定方向的“投射”算法。代理在景观中的随机位置和方向启动,并允许移动,直到它们到达气味源(成功)或离开成像区域(失败)。算法的参数选择是为了优化成功率和最小化到源的路径长度。在空气羽流中,成功率超过 90%,路径长度可以低至距离源起始距离的两倍,而在高度湍流的水羽流中,路径长度可以低至距离源起始距离的四倍。我们发现,优化成功率的参数通常会导致更具探索性的通往源的路径。关于气味来自哪个方向的信息对于在水羽流中成功导航是必要的,并减少了在三个测试的空气羽流中的路径长度。