Data fusion for compliant motion tasks based on human skills
نویسندگان
چکیده
The paper discusses new developments of the data fusion paradigm presented in [3], [4]. A bank of Kalman filters is analyzed in the fusion process. Experiments for a robotic compliant motion task (pegin-hole) emerged from human skills are reported. Stereo vision and pose sense are fused to execute the task. Feedforward artificial neural networks (ANNs) are trained to transfer human skills to robotic manipulators.
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تاریخ انتشار 2002