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Based on our previous work, this paper proposes an improved robotic door-opening framework. The improved framework has three components, grasping pattern, door-opening pattern, and semantic monitoring and exception handling. (1) Grasping pattern contains various grasping points and ways for different types of door knob. The point cloud of the target area is captured using Kinect sensor, and the door...
Robots in dynamic and uncertain environments are vulnerable to mission failures due to external perturbation or internal malfunctions. Diagnosis is the process to detect, locate or even assess the fault. Since robots rely on their function modules to sense the external environment, it is difficult to locate the fault under uncertainties of robot components. The situation can be worse when there is...
Non-contact, non-invasive monitoring of hemodynamic parameters would be ideal for medical monitoring in a variety of environments. Radio Frequency Impedance Interrogation (RFII) measures hemodynamic function via resonance frequency coupling to a hydrophilic protein molecule. While the application of this technology to hemodynamic monitoring has demonstrated initial success, this preliminary study...
A method of pattern recognition of tool wear based on Discrete Hidden Markov Models (DHMM) is proposed to monitor tool wear and to predict tool failure. FFT features are first extracted from the vibration signal and cutting force in cutting process, and then FFT vectors are presorted and converted into integers by SOM. Finally, these codes are introduced to DHMM for machine learning and 3 models for...
A method of pattern recognition of tool wear based on Discrete Hidden Markov Models (DHMM) is proposed to monitor tool wear and to predict tool failure. At the first FFT features are extracted from the vibration signal and cutting force in cutting process, then FFT vectors are presorted and coded into code book of integer numbers by SOM, and these code books are introduced to DHMM for machine learning...
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