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Marcello Calisti

Researcher at Sant'Anna School of Advanced Studies

Publications -  59
Citations -  2117

Marcello Calisti is an academic researcher from Sant'Anna School of Advanced Studies. The author has contributed to research in topics: Robot & Soft robotics. The author has an hindex of 17, co-authored 51 publications receiving 1447 citations. Previous affiliations of Marcello Calisti include University of Lincoln & University of Florence.

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An octopus-bioinspired solution to movement and manipulation for soft robots.

TL;DR: This study investigates the smart solution that the Octopus vulgaris adopts to perform a crawling movement, with the same limbs used for grasping and manipulation, with a suitable way to build a more complex soft robot that, with minimum control, can perform diverse tasks.
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Dynamic Model of a Multibending Soft Robot Arm Driven by Cables

TL;DR: A dynamic model of a continuum soft robot arm driven by cables and based upon a rigorous geometrically exact approach is developed, which fully investigates both dynamic interaction with a dense medium and the coupled tendon condition.
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Bioinspired locomotion and grasping in water: the soft eight-arm OCTOPUS robot.

TL;DR: The experimental results show that the octopus-inspired robot can walk in water using the same strategy as the animal model, with good performance over different surfaces, including walking through physical constraints.
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Fundamentals of soft robot locomotion.

TL;DR: This paper aims to provide a reference guide for researchers approaching mobilesoft robotics, to describe the underlying principles of soft robot locomotion with its pros and cons, and to envisage applications and further developments for mobile soft robotics.
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Neural Network and Jacobian Method for Solving the Inverse Statics of a Cable-Driven Soft Arm With Nonconstant Curvature

TL;DR: This study presents both a model-based method and a supervised learning method to solve the inverse statics of nonconstant curvature soft manipulators and chooses a Jacobian-based and a feedforward neural network to solve this problem.