Robotic skills learning based on dynamical movement primitives using a wearable device - Details

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Abstract：

It　is　an　effective　way　for　the　robots　to　learn　operation　skills　from　the　humans.　In　this　paper,　we　realize　a　skill　learning　system　based　on　a　teleportation　system　for　transferring　the　human　experience　to　the　robot.　Firstly,　the　robotic　teleoperation　system　with　a　wearable　device　is　developed　by　controlling　the　motor　speed　directly.　This　system　greatly　reduces　the　time　delay　by　comparing　with　the　way　that　controlling　with　point　position.　Then,　a　rotation　invariant　dynamical　movement　primitive　method　is　presented　for　learning　the　operation　skills.　Finally,　the　effectiveness　of　the　proposed　human　experience　learning　system　is　evaluated　by　experiments　on　a　Baxter　robot.　The　human-robot　interaction　experiment　shows　the　validity　of　the　presented　robotic　skill　learning　system.　©　2017　IEEE.

Keyword：

Biomimetics Human robot interaction Learning systems Remote control Robotics Wearable technology

Community：

[ 1 ] [Wei, Xiang]College of Mathematics and Computer Science, Fuzhou University, Fuzhou; 350116, China
[ 2 ] [Sun, Fuchun]College of Mathematics and Computer Science, Fuzhou University, Fuzhou; 350116, China
[ 3 ] [Sun, Fuchun]Tsinghua National Laboratory for Information Science and Technology, State Key Lab on Intelligence and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing; 100084, China
[ 4 ] [Yu, Yuanlong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou; 350116, China
[ 5 ] [Liu, Chunfang]Tsinghua National Laboratory for Information Science and Technology, State Key Lab on Intelligence and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing; 100084, China
[ 6 ] [Fang, Bin]Tsinghua National Laboratory for Information Science and Technology, State Key Lab on Intelligence and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing; 100084, China
[ 7 ] [Jing, Mingxuan]Tsinghua National Laboratory for Information Science and Technology, State Key Lab on Intelligence and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing; 100084, China

Reprint 's Address：

孙富春
[sun, fuchun]college of mathematics and computer science, fuzhou university, fuzhou; 350116, china;;[sun, fuchun]tsinghua national laboratory for information science and technology, state key lab on intelligence and technology, department of computer science and technology, tsinghua university, beijing; 100084, china

Email：

fcsun@mail.tsinghua.edu.cn

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