Tracking Object's Pose via Dynamic Tactile Interaction

被引:0
|
作者
Lin, Qiguang [1 ]
Yan, Chaojie [2 ]
Li, Qiang [3 ]
Ling, Yonggen [4 ]
Lee, Wangwei [4 ]
Zheng, Yu [4 ]
Wan, Zhaoliang [5 ]
Huang, Bidan [4 ]
Liu, Xiaofeng [1 ]
机构
[1] Hohai Univ, Coll IoT Engn, Jiangsu Key Lab Special Robot Technol, Changzhou 213022, Jiangsu, Peoples R China
[2] Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control & Technol, R China, Hangzhou, Peoples R China
[3] Shenzhen Technol Univ, Coll Big Data & Internet, Shenzhen 518118, Peoples R China
[4] Tencent Robot X, Shenzhen, Peoples R China
[5] Sun Yat Sen Univ, Sch Comp Sci & Engn, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Tactile perception; robotic grasping; extended Kalman filter;
D O I
10.1142/S0219843623500214
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
It is a challenging task to localize and track an in-hand object in robotic domain. Researchers were mainly using the vision as major modality for extracting object's pose. The vision approaches are fragile when the object is occluded by the robotic arm and hand. To this end, we propose a tactile-based DTI-Tracker (tracking object's pose via Dynamic Tactile Interaction) approach and formalize the object's tracking as a filter problem. An Extended Kalman Filter (EKF) is used to estimate the in-hand object pose exploiting the high spatial resolution tactile feedback. Given the initial estimation error, the proposed approach rapidly converges the estimation result to the real pose and the statistic evaluation shows the robustness of the proposed approach. We evaluate this method in physics simulation and real multi-fingered grasping setup while the object is static and movable. The proposed method is a potential tool to foster future research on dexterous manipulation using multifingered robotic hand.
引用
收藏
页数:22
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