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用于判别连接状态的机器人手爪多传感器数据融合
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2009-07-17
h1654155957.9921
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舱外移动机器人在空间站工作时,其手爪与工件及空间站的安全连接至关重要。分别用BP
神经网络和径向基函数神经网络,对机器人手爪上的力传感器、接近觉传感器和位移传感器的信息进行了融合,得到一个关于机器人手爪连接状态的正确判别。
关键词: 机器人手爪; 多传感器数据融合; 神经网络
Abstract : When an extravehicular mobile robot (EMR) is working in the space station , it is very important for grippers to connect to objects or the space station firmly. The output data of force sensors , proximity sensors and a displacement sensor are fused using back2propagation artificial neural network and radial basis function artificial neural network to obtain the accurate information of the gripper connection states.
Key words : Robotic gripper ; Multi2sensor data fusion ; Artificial neural network
神经网络和径向基函数神经网络,对机器人手爪上的力传感器、接近觉传感器和位移传感器的信息进行了融合,得到一个关于机器人手爪连接状态的正确判别。
关键词: 机器人手爪; 多传感器数据融合; 神经网络
Abstract : When an extravehicular mobile robot (EMR) is working in the space station , it is very important for grippers to connect to objects or the space station firmly. The output data of force sensors , proximity sensors and a displacement sensor are fused using back2propagation artificial neural network and radial basis function artificial neural network to obtain the accurate information of the gripper connection states.
Key words : Robotic gripper ; Multi2sensor data fusion ; Artificial neural network
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