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A method to measure 3D positions of elevator buttons from a mobile robot using a 2D artificial landmark, a laser navigation system and a competitive neural net

机译:一种使用2D人工地标,激光导航系统和竞争性神经网络从移动机器人测量电梯按钮3D位置的方法

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This article describes a new method to measure 3D positions of elevator buttons from the mobile guard robot which we have developed in order for the robot to autonomously get on and off the conventional elevators of a building for patrolling different floors. ne measurement system uses a single camera on the robot and a 2D artificial landmark on the wall holding the elevator buttons, and it also takes advantage of the laser navigation system which enables the robot to stop facing the wall. Since the images captured by the camera mounted at the front body of the robot consisted of perspective patterns of the wall, we utilizes two neural schemes: one is the competitive neural net for pattern recognition invariant to projective transformations, and the other is the competitive learning scheme for vector quantization in order to obtain efficient template patterns. We also develop a method to calculate the 3D positions of the elevator buttons and examine the measurement errors for the robot to push the buttons.
机译:本文介绍了一种新的方法,该方法可以测量移动警卫机器人的电梯按钮的3D位置,我们已经开发了该方法,以使机器人能够自动上下建筑物的传统电梯,以在不同楼层巡逻。测量系统在机器人上使用单个摄像头,并在固定电梯按钮的墙上使用2D人工地标,并且还利用了激光导航系统,该系统可使机器人停止面对墙。由于安装在机器人前部机身上的摄像头捕获的图像是由墙壁的透视图组成的,因此我们采用了两种神经网络方案:一种是竞争性神经网络,用于模式转化为投影变换,而另一种是竞争性学习用于矢量量化的方案以获得有效的模板模式。我们还开发了一种计算电梯按钮3D位置并检查机器人按下按钮的测量误差的方法。

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