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Event-Based Target Tracking Control for a Snake Robot Using a Dynamic Vision Sensor

机译:使用动态视觉传感器的蛇机器人基于事件的目标跟踪控制

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Dynamic Vision Sensor (DVS) is a promising neuromorphic vision sensor for autonomous locomotion control of mobile robots, as the DVS acquires visual information by mimicking retina to sense and encode the world as neural signals. In this paper, we present an autonomous target detecting and tracking control approach for a snake-like robot with a monocular DVS. By using Hough transform based on the Spiking Neural Network (SNN), the target pole is detected as two parallel lines from the event-based visual input. Then a depth estimation method based on the pose and motion of the robot is proposed. Furthermore, by combining the periodic motion feature of the snake-like robot, an adaptive tracking method based on the estimated depth information is introduced. Experiments are conducted on a snake-like robot to demonstrate the practicality and accuracy of our proposed method to track a target pole dynamically with a monocular DVS.
机译:动态视觉传感器(DVS)是一种有前途的神经形态视觉传感器,可用于移动机器人的自主运动控制,因为DVS通过模仿视网膜以将世界感知并编码为神经信号来获取视觉信息。在本文中,我们提出了一种具有单眼DVS的蛇状机器人的自主目标检测和跟踪控制方法。通过使用基于尖峰神经网络(SNN)的霍夫变换,可以从基于事件的视觉输入中将目标极点检测为两条平行线。提出了一种基于机器人姿态和运动的深度估计方法。此外,通过结合蛇形机器人的周期性运动特征,引入了一种基于估计深度信息的自适应跟踪方法。在蛇形机器人上进行了实验,以证明我们提出的用单眼DVS动态跟踪目标极点的方法的实用性和准确性。

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