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Thrishantha Nanayakkara

Researcher at Imperial College London

Publications -  151
Citations -  2567

Thrishantha Nanayakkara is an academic researcher from Imperial College London. The author has contributed to research in topics: Computer science & Palpation. The author has an hindex of 24, co-authored 133 publications receiving 2021 citations. Previous affiliations of Thrishantha Nanayakkara include Johns Hopkins University & Harvard University.

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Proceedings ArticleDOI

Design of a variable stiffness flexible manipulator with composite granular jamming and membrane coupling

TL;DR: The design of a snake-like laboratory made soft robot manipulator of 20 mm in average diameter is presented, which can actuate, soften, or stiffen joints independently along the length of the manipulator by combining granular jamming with McKibben actuators.
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A Real-Time State Predictor in Motor Control: Study of Saccadic Eye Movements during Unseen Reaching Movements

TL;DR: In unperturbed reaching movements, saccade occurrence at any timet consistently provided an unbiased estimate of hand position at t + 196 msec, and the ability of the brain to guide saccades to the future position of the hand failed when a force field unexpectedly changed the dynamics of theHand immediately after perturbation.
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Implementation of Tactile Sensing for Palpation in Robot-Assisted Minimally Invasive Surgery: A Review

TL;DR: The objective of this paper is to review the latest advancements and challenges in the development of tactile sensing devices designed for surgical applications, focusing on palpation and probing devices that can be potentially used in RMIS.
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Robust real time material classification algorithm using soft three axis tactile sensor: Evaluation of the algorithm

TL;DR: A texture classification algorithm utilizing support vector machine (SVM) classifier utilizing a novel three axis tactile sensor that utilize magnetic flux measurements for transduction was used to obtain three dimensional tactile data.
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Primitives for motor adaptation reflect correlated neural tuning to position and velocity.

TL;DR: It is shown that correlated tuning explains why initial stages of motor learning are often rapid and stereotyped, whereas later stages are slower and stimulus specific, suggesting a theoretical basis for the rational design of improved procedures for motor training and rehabilitation.