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Related publications (1,000)

Page 13 of 100

Identification of the trade-off between speed and efficiency in undulatory swimming using a bio-inspired robot

Auke Ijspeert, Karen Ann J Mulleners, Kamilo Andres Melo Becerra, Alexandros Anastasiadis, Laura Isabel Paez Coy, Eric Daniel Tytell

Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body’s kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to livin ...

2023

Effects of Head-Tracking Artefacts on Externalization and Localization in Azimuth With Binaural Wearable Devices

Hervé Lissek, Gilles André Courtois, Vincent Pierre Olivier Grimaldi

Head tracking combined with head movements have been shown to improve auditory externalization of a virtual sound source and contribute to the performance in localization. With certain technically constrained head-tracking algorithms, as can be found in we ...

New York2023

Enabling four-arm laparoscopic surgery by controlling two robotic assistants via haptic foot interfaces

Aude Billard, Mohamed Bouri, Walid Amanhoud, Jacob Hernandez Sanchez

Robotic surgery is a promising direction to improve surgeons and assistants’ daily life with respect to conventional surgery. In this work, we propose solo laparoscopic surgery in which two robotic arms, controlled via haptic foot interfaces, assist the ta ...

2023

Owing to stochastic fluctuations arising from finite population size, known as genetic drift, the ability of a population to explore a rugged fitness landscape depends on its size. In the weak mutation regime, while the mean steady-state fitness increases ...

ROYAL SOC2023

Time Series Analysis of Urban Liveability

Devis Tuia, Diego Marcos Gonzalez, Alex Hubertus Levering

In this paper we explore deep learning models to monitor longitudinal liveability changes in Dutch cities at the neighbourhood level. Our liveability reference data is defined by a country-wise yearly survey based on a set of indicators combined into a liv ...

IEEE2023

Exploring neural networks and their potential for species distribution modeling

Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Lloyd Haydn Hughes

Species distribution models (SDMs) relate species occurrence data with environmental variables and are used to understand and predict species distributions across landscapes. While some machine learning models have been adopted by the SDM community, recent ...

2023

Sensing forms an integral part of soft matter based robots due to their compliance, dependence on loading conditions, and virtually infinite degrees of freedom. Previous studies have developed several extrinsic sensors and embedded them into soft actuators ...

ROYAL SOC CHEMISTRY2023

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

Jean-Philippe Thiran, Guillaume Marc Georges Vray, Devavrat Tomar

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Tes ...

IEEE2023

Exploiting Kinematic Redundancy for Robotic Grasping of Multiple Objects

Aude Billard, Kunpeng Yao

Humans coordinate the abundant degrees of freedom (DoFs) of hands to dexterously perform tasks in everyday life. We imitate human strategies to advance the dexterity of multi-DoF robotic hands. Specifically, we enable a robot hand to grasp multiple objects ...

2023

Networked Signal and Information Processing: Learning by multiagent systems

Ali H. Sayed, Stefan Vlaski

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023