Spiking Elementary Motion Detector in Neuromorphic Systems
Spiking Elementary Motion Detector in Neuromorphic Systems
复制标题
DOI：
10.1162/neco_a_01112
复制
发表时间：
2018-08
影响因子：
2.9
通讯作者：
Moritz B. Milde;O. Bertrand;H. Ramachandran;M. Egelhaaf;E. Chicca
中科院分区：
文献类型：
--
作者：
Moritz B. Milde;O. Bertrand;H. Ramachandran;M. Egelhaaf;E. Chicca
智能体视网膜上周围环境的明显运动可用于在杂乱的环境中导航，避免与障碍物碰撞，或跟踪感兴趣的目标。物体的视运动模式（即，光流）包含关于周围环境的空间信息。对于搜索和救援任务中使用的小型快速移动代理，估计与附近物体的距离以快速避免碰撞至关重要。在给定必要硬件的大小、功率和延迟约束的情况下，这种估计不能通过常规方法（诸如基于帧的光流估计）来完成。一种实用的替代方案是使用基于事件的视觉传感器。与基于帧的方法相反，它们只在视觉场景发生变化时才产生所谓的事件。我们提出了一种新的异步电路，尖峰基本运动检测器（SEMD），由一个单一的硅神经元和突触，检测基本运动从基于事件的视觉传感器。sEMD将物体图像穿过视网膜所需的时间编码为一系列尖峰。爆发内的尖峰数量与事件穿过视网膜的速度成比例。一个快速但不精确的旅行时间的估计已经可以从一个突发的前两个尖峰获得，并通过随后的尖峰间期进行细化。由于自适应非线性突触功效缩放，后一种编码方案是可能的。我们表明，sEMD可以用来计算在混乱的室外环境中的机器人导航的背景下，避免碰撞的方向，并比较基于帧的算法的避免碰撞的方向。所提出的计算原理构成了可以应用于其他感觉模态（例如，声音定位），它提供了一个新的视角，门控信息尖峰神经网络。
Apparent motion of the surroundings on an agent's retina can be used to navigate through cluttered environments, avoid collisions with obstacles, or track targets of interest. The pattern of apparent motion of objects, (i.e., the optic flow), contains spatial information about the surrounding environment. For a small, fast-moving agent, as used in search and rescue missions, it is crucial to estimate the distance to close-by objects to avoid collisions quickly. This estimation cannot be done by conventional methods, such as frame-based optic flow estimation, given the size, power, and latency constraints of the necessary hardware. A practical alternative makes use of event-based vision sensors. Contrary to the frame-based approach, they produce so-called events only when there are changes in the visual scene. We propose a novel asynchronous circuit, the spiking elementary motion detector (sEMD), composed of a single silicon neuron and synapse, to detect elementary motion from an event-based vision sensor. The sEMD encodes the time an object's image needs to travel across the retina into a burst of spikes. The number of spikes within the burst is proportional to the speed of events across the retina. A fast but imprecise estimate of the time-to-travel can already be obtained from the first two spikes of a burst and refined by subsequent interspike intervals. The latter encoding scheme is possible due to an adaptive nonlinear synaptic efficacy scaling. We show that the sEMD can be used to compute a collision avoidance direction in the context of robotic navigation in a cluttered outdoor environment and compared the collision avoidance direction to a frame-based algorithm. The proposed computational principle constitutes a generic spiking temporal correlation detector that can be applied to other sensory modalities (e.g., sound localization), and it provides a novel perspective to gating information in spiking neural networks.