Sökning: onr:"swepub:oai:DiVA.org:kth-336851" > Bioinspired Co-Desi...
Fältnamn | Indikatorer | Metadata |
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000 | 04156naa a2200457 4500 | |
001 | oai:DiVA.org:kth-336851 | |
003 | SwePub | |
008 | 230920s2022 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3368512 URI |
024 | 7 | a https://doi.org/10.1002/aisy.2022000502 DOI |
040 | a (SwePub)kth | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a art2 swepub-publicationtype |
100 | 1 | a Kong, Depengu Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
245 | 1 0 | a Bioinspired Co-Design of Tactile Sensor and Deep Learning Algorithm for Human-Robot Interaction |
264 | c 2022-04-26 | |
264 | 1 | b Wiley,c 2022 |
338 | a print2 rdacarrier | |
500 | a QC 20230920 | |
520 | a Robots equipped with bionic skins for enhancing the robot perception capability are increasingly deployed in wide applications ranging from healthcare to industry. Artificial intelligence algorithms that can provide bionic skins with efficient signal processing functions further accelerate the development of this trend. Inspired by the somatosensory processing hierarchy of humans, the bioinspired co-design of a tactile sensor and a deep learning-based algorithm is proposed herein, simplifying the sensor structure while providing computation-enhanced tactile sensing performance. The soft piezoresistive sensor, based on the carbon black-coated polyurethane sponge, offers a continuous sensing area. By utilizing a customized deep neural network (DNN), it can detect external tactile stimulus spatially continuously. Besides, a novel data augmentation method is developed based on the sensor's hexagonal structure that has a sixfold rotation symmetry. It can significantly enhance the generalization ability of the DNN model by enriching the collected training data with generated pseudo-data. The functionality of the sensor and the robustness of the proposed data augmentation strategy are verified by precisely recognizing five touch modalities, illustrating a well-generalized performance, and providing a promising application prospect in human-robot interaction. | |
650 | 7 | a TEKNIK OCH TEKNOLOGIERx Elektroteknik och elektronikx Robotteknik och automation0 (SwePub)202012 hsv//swe |
650 | 7 | a ENGINEERING AND TECHNOLOGYx Electrical Engineering, Electronic Engineering, Information Engineeringx Robotics0 (SwePub)202012 hsv//eng |
653 | a data augmentation | |
653 | a deep learning | |
653 | a human-robot interaction | |
653 | a tactile sensor | |
700 | 1 | a Yang, Gengu Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Pang, Gaoyangu Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia.4 aut |
700 | 1 | a Ye, Zhiqiuu Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Lv, Honghaou Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Yu, Zhangweiu Zhejiang Normal Univ, Hangzhou Inst Adv Studies, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Wang, Feiu China Acad Art, Sch Design & Art, Dept Ind Design, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Wang, Xi Vincent,c Dr.d 1985-u KTH,Produktionsutveckling4 aut0 (Swepub:kth)u1za3gdg |
700 | 1 | a Xu, Kaichenu Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
700 | 1 | a Yang, Huayongu Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.4 aut |
710 | 2 | a Zhejiang Univ, Sch Mech Engn, State Key Lab Fluid Power & Mechatron Syst, Hangzhou 310027, Peoples R China.b Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia.4 org |
773 | 0 | t ADVANCED INTELLIGENT SYSTEMSd : Wileyg 4:6q 4:6x 2640-4567 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-336851 |
856 | 4 8 | u https://doi.org/10.1002/aisy.202200050 |
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