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Fang, G. (author), Tian, Yingjun (author), Yang, Zhi Xin (author), Geraedts, Jo M.P. (author), Wang, C.C. (author)
This article presents an efficient learning-based method to solve the <italic>inverse kinematic</italic> (IK) problem on soft robots with highly nonlinear deformation. The major challenge of efficiently computing IK for such robots is due to the lack of analytical formulation for either forward or inverse kinematics. To address...
journal article 2022
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Fang, G. (author), Tian, Yingjun (author), Weightman, Andrew (author), Wang, C.C. (author)
Soft robots can safely interact with environments because of their mechanical compliance. Self-collision is also employed in the modern design of soft robots to enhance their performance during different tasks. However, developing an efficient and reliable simulator that can handle the collision response well, is still a challenging task in...
conference paper 2022
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Wang, F. (author), Tian, Zhi (author), Leus, G.J.T. (author), Fang, Jun (author)
In this paper, we study the problem of wideband direction of arrival (DoA) estimation with sparse linear arrays (SLAs), where a number of uncorrelated wideband signals impinge on an SLA and the data is collected from multiple frequency bins. To boost the performance and perform underdetermined DoA estimation, the difference co-array response...
journal article 2021
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Wang, F. (author), Tian, Zhi (author), Fang, Jun (author), Leus, G.J.T. (author)
This paper concerns wideband direction of arrival (DoA) estimation with sparse linear arrays (SLAs). We rely on the assumption that the power spectrum of the wideband sources is the same up to a scaling factor, which could in theory allow us to resolve not only more sources than the number of antennas but also more sources than the number of...
conference paper 2020
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