D
David Navarro-Alarcon
Researcher at Hong Kong Polytechnic University
Publications - 109
Citations - 1174
David Navarro-Alarcon is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Computer science & Robot. The author has an hindex of 12, co-authored 88 publications receiving 682 citations. Previous affiliations of David Navarro-Alarcon include The Chinese University of Hong Kong & CINVESTAV.
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Journal ArticleDOI
Automatic 3-D Manipulation of Soft Objects by Robotic Arms With an Adaptive Deformation Model
David Navarro-Alarcon,Hiu Man Yip,Zerui Wang,Yun-Hui Liu,Fangxun Zhong,Tianxue Zhang,Peng Li +6 more
TL;DR: A new feedback method to automatically servo-control the 3-D shape of soft objects with robotic manipulators by computes in real time the unknown deformation parameters of a soft object; this algorithm provides a valuable adaptive behavior to the deformation controller, something the authors cannot achieve with traditional fixed-model approaches.
Journal ArticleDOI
Fourier-Based Shape Servoing: A New Feedback Method to Actively Deform Soft Objects into Desired 2-D Image Contours
David Navarro-Alarcon,Yunhui Liu +1 more
TL;DR: The design of a vision-based method to automatically deform soft objects into desired two-dimensional shapes with robot manipulators is addressed, with an innovative feedback representation of the object's shape based on a truncated Fourier series.
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Model-Free Visually Servoed Deformation Control of Elastic Objects by Robot Manipulators
TL;DR: This paper derives a new dynamic-state feedback velocity control law using the passivity-based framework and proves that even in the presence of inexact estimations, the closed-loop dynamical system ensures input-to-state stability with respect to external disturbances.
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On the visual deformation servoing of compliant objects: Uncalibrated control methods and experiments
TL;DR: Two new visual servoing approaches to explicitly servo-control elastic deformations are presented, both of which provide a way to automatically control deformations in a model-free manner.
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Vision-based manipulation of deformable and rigid objects using subspace projections of 2D contours
TL;DR: In this article, a unified vision-based manipulation framework using image contours of deformable/rigid objects is proposed, which allows the robot to manipulate an object without knowing whether it is rigid or deformable.