首页|Studies from Sun Yat-sen University Describe New Findings in Machine Learning (Flexible Artificial Tactility With Excellent Robustness and Temperature Tolerance Based On Organohydrogel Sensor Array for Robot Motion Detection and Object Shap e ...)
Studies from Sun Yat-sen University Describe New Findings in Machine Learning (Flexible Artificial Tactility With Excellent Robustness and Temperature Tolerance Based On Organohydrogel Sensor Array for Robot Motion Detection and Object Shap e ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting out of Guangzhou, People's Republic of C hina, by NewsRx editors, research stated, "Hydrogel-based flexible artificial ta ctility is equipped to intelligent robots to mimic human mechanosensory percepti on. However, it remains a great challenge for hydrogel sensors to maintain flexi bility and sensory performances during cyclic loadings at high or low temperatur es due to water loss or freezing." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news journalists obtained a quote from the research from Sun Yat-sen Univers ity, "Here, a flexible robot tactility is developed with high robustness based o n organohydrogel sensor arrays with negligent hysteresis and temperature toleran ce. Conductive polyaniline chains are interpenetrated through a poly(acrylamide-co-acrylic acid) network with glycerin/water mixture with interchain electrostat ic interactions and hydrogen bonds, yielding a high dissipated energy of 1.58 MJ m-3, and ultralow hysteresis during 1000 cyclic loadings. Moreover, the binary solvent provides the gels with outstanding tolerance from -100 to 60 degrees C a nd the organohydrogel sensors remain flexible, fatigue resistant, conductive (0. 27 S m-1), highly strain sensitive (GF of 3.88) and pressure sensitive (35.8 MPa -1). The organohydrogel sensor arrays are equipped on manipulator finger dorsa a nd pads to simultaneously monitor the finger motions and detect the pressure dis tribution exerted by grasped objects. A machine learning model is used to train the system to recognize the shape of grasped objects with 100% acc uracy. The flexible robot tactility based on organohydrogels is promising for no vel intelligent robots. The robust and flexible artificial tactility enabled by a tough, low-hysteresis organohydrogel sensor array ensures precise detection of robot motion and external pressure over broad temperature range."
GuangzhouPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNano-robotRobotRoboti csSun Yat-sen University
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