Tao Sun

Prof. Dr. Tao Sun


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2016 in Robotics and Computer-Integrated Manufacturing
Verified
Journal Article
Closed access
TSTao Sun
Tao Sun
YZYapu Zhai
Yapu Zhai
YSYimin Song
Yimin Song
JZJiateng Zhang
Jiateng Zhang

25 February 2020 in IEEE Transactions on Robotics
Verified
Journal Article
Closed access
TSTao Sun
Tao Sun
BLBinbin Lian
Binbin Lian
Shuofei YangShuofei Yang
Shuofei Yang
YSYimin Song
Yimin Song
In current robot calibration approaches, the error propagation and identification of serial and parallel robots fail to be solved intuitively and generically, resulting in an inefficient calibration implementation and a low accuracy improvement. In this article, we present a generic error modeling method of serial robots and extend to parallel robots by finite and instantaneous screw (FIS) theory. The differential map and the explicit description of FIS on the robot motions enable a concise error modeling of the serial robot. The identifiability of errors in serial robot is discussed. The maximum independent errors are proved to be 4r + 2p + 6, where r and p are the numbers of revolute and prismatic joints, respectively. Based on the error mapping of serial limbs, reciprocal twist and wrench are introduced to consider the interaction among limbs and reveal the error propagation of the parallel robot. Then, the identification algorithms with high robustness and efficiency are investigated for the serial and parallel robots. Specifically, the conventional ill-conditioning problems of parallel robots are addressed. Finally, the proposed kinematic calibration framework for both types of robots are compared with the existing methods, and verified by simulations and experiments. The results show that our calibration approach improves the robot accuracy in a robust and efficient manner.

1 August 2015 in International Journal of Machine Tools and Manufacture
Verified
Journal Article
Open access
BLBinbin Lian
Binbin Lian
TSTao Sun
Tao Sun
YSYimin Song
Yimin Song
YJYan Jin
Yan Jin
MPMark Price
Mark Price

1 December 2017 in Robotics and Autonomous Systems
Verified
Journal Article
Closed access
TSTao Sun
Tao Sun
XXXu Xiang
Xu Xiang
WSWeihua Su
Weihua Su
HWHang Wu
Hang Wu
YSYimin Song
Yimin Song

1 February 2018 in Mechanism and Machine Theory
Verified
Journal Article
Closed access
TSTao Sun
Tao Sun
BLBinbin Lian
Binbin Lian

29 September 2017 in IEEE Transactions on Industrial Electronics
Verified
Journal Article
Closed access
TSTao Sun
Tao Sun
DLDong Liang
Dong Liang
YSYimin Song
Yimin Song
High-speed robots are being applied more and more widely in the scenarios of aviation manufacturing, electronic packaging, and three-dimensional printing, etc. To achieve high speed, the robots are typically designed to be lightweight, hence suffer from undesired vibration, so that the dynamic performance would deteriorate. In light of this, this paper considers the dynamic modeling and active control of an emerging redundant parallel robot. First, the recursively dynamic model is modularly established by means of Lagrangian multipliers method. For completeness, the model of permanent magnet synchronous motor is further integrated with the model of mechanical system to formulate the electromechanically coupled dynamic model (ECDM). To facilitate dynamic control, the ECDM is cleverly projected into the null space of constraint Jacobian matrix eliminating the need to compute Lagrangian multipliers explicitly. Based on singular perturbation approach and Tikhonov theorem, the ECDM is decomposed into two subsystems in different timescales. On this basis, a nonlinear hybrid control scheme is proposed for both trajectory tracking and vibration suppression. Numerical simulations suggest that the nonlinear hybrid control exhibits overwhelming performance than the conventional joint-based proportional and differential feedback control.