Yunhui Liu

Yunhui Liu


Research Focus & Metrics

Academic Career Length

36Years (1991-Present)

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

Representative Publications

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19 November 2020
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JWJiangliu Wang
Jiangliu Wang
JJJianbo Jiao
Jianbo Jiao
YLYunhui Liu
Yunhui Liu

13 November 2017 in IEEE Transactions on Robotics
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Journal Article
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David Navarro-AlarconDavid Navarro-Alarcon
David Navarro-Alarcon
YLYunhui Liu
Yunhui Liu
This paper addresses the design of a vision-based method to automatically deform soft objects into desired two-dimensional shapes with robot manipulators. The method presents an innovative feedback representation of the object’s shape (based on a truncated Fourier series) and effectively exploits it to guide the soft object manipulation task. A new model calibration scheme that iteratively approximates a local deformation model from vision and motion sensory feedback is derived; this estimation method allows us to manipulate objects with unknown deformation properties. Pseudocode algorithms are presented to facilitate the implementation of the controller. Numerical simulations and experiments are reported to validate this new approach.

18 December 2017 in IEEE Transactions on Robotics
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Journal Article
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XLXinwu Liang
Xinwu Liang
Hesheng WangHesheng Wang
Hesheng Wang
YLYunhui Liu
Yunhui Liu
WCWeidong Chen
Weidong Chen
Tao LiuTao Liu
Tao Liu
Most existing formation control approaches are based on the assumption that the global/relative position and/or velocity measurements of mobile robots are directly available. To extend the application domain and to improve the formation control performance, it is extremely necessary to avoid the use of position and velocity measurements in the design of formation controllers. In this paper, we propose new leader-following formation tracking control schemes for nonholonomic mobile robots with onboard perspective cameras, without using both position and velocity measurements. To address the unavailability issue of position measurements, the leader–follower kinematics model in the image space is developed, which can facilitate the complete elimination of measurement/estimation of the position information. Furthermore, feedback information from the perspective camera of the follower robot is used to design adaptive observers to estimate the leader linear velocity for feedforward compensation, which can handle the absence of velocity measurements such that the proposed schemes can be applied to control formations of mobile robots without mutual communication abilities. By using the Lyapunov stability theory, a rigorous stability analysis based on the nonlinear formation dynamics is provided to show that the global stability of the combined observer–controller closed-loop system can be guaranteed. Both simulation and experimental results are also given to demonstrate the performance of the proposed formation tracking control schemes.

17 September 2022
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Book Chapter
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ZWZiyi Wang
Ziyi Wang
BLBo Lu
Bo Lu
YLYonghao Long
Yonghao Long
FZFangxun Zhong
Fangxun Zhong
TCTak-Hong Cheung
Tak-Hong Cheung
YLYunhui Liu
Yunhui Liu

23 June 2022 in Proceedings of the IEEE
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Journal Article
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PFPaolo Fiorini
Paolo Fiorini
KGKen Y. Goldberg
Ken Y. Goldberg
YLYunhui Liu
Yunhui Liu
RTRussell H. Taylor
Russell H. Taylor
Surgical robots have been widely adopted with over 4000 robots being used in practice daily. However, these are telerobots that are fully controlled by skilled human surgeons. Introducing “surgeon-assist”—some forms of autonomy—has the potential to reduce tedium and increase consistency, analogous to driver-assist functions for lane-keeping, cruise control, and parking. This article examines the scientific and technical backgrounds of robotic autonomy in surgery and some ethical, social, and legal implications. We describe several autonomous surgical tasks that have been automated in laboratory settings, and research concepts and trends.

1 February 2000 in The International Journal of Robotics Research
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Journal Article
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YLYunhui Liu
Yunhui Liu
This paper presents an efficient algorithm for computing all n-finger form-closure grasps on a polygonal object based on a new sufficient and necessary condition for form-closure. With this new condition, it is possible to transfer the problem of computing the form-closure grasp in R3 to one in R1. We demonstrate that the non-form-closure grasps consist of two convex polytopes in the space of n parameters representing grasp points on sides of the polygon. The proposed algorithm works efficiently for n ≤ 3 and takes O(n3n/2) time for n > 3, where n denotes the number of the fingers. The algorithm has been implemented and its efficiency has been confirmed with two examples.