Jaime Valls Miro

Associate Professor

University of Sydney

Australia

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Dr. Jaime Valls Miro is an Associate Professor at the University of Technology Sydney, Australia. His research focuses on human-machine interaction, artificial intelligence, robotics, and advanced sensor technologies. He has published extensively on topics including motion planning for UAVs, water leak detection using vibro-acoustic signals, and optimal path planning for robotic manipulators.

Articles (15)

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2025

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2020

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2020

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2020

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2020

Collaborators (4)

Lili Bykerk

University of Sydney

AUSTRALIA

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Arturo Gil

Profesor Titular de Universidad

Universidad Miguel Hernández de Elche

SPAIN

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Ernesto Solanes

Profesor Ayudante Doctor

Universitat Politècnica de València

SPAIN

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Sarath Kodagoda

University of Sydney

AUSTRALIA

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Jaime Valls Miro

Research Interests

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About

Articles (15)

An Improved Maximal Continuity Graph Solver for Non-Redundant Manipulator Non-Revisiting Coverage

Marden-Based Homotopic Enclosed Safe Motion Corridor Generation for UAV Navigation in Complex Environments

Advances in Human–Machine Interaction, Artificial Intelligence, and Robotics

Multimodel Neural Network for Live Classification of Water Pipe Leaks from Vibro-Acoustic Signals

Template-Free Nonrevisiting Uniform Coverage Path Planning on Curved Surfaces

Vibro-Acoustic Distributed Sensing for Large-Scale Data-Driven Leak Detection on Urban Distribution Mains

Detection of Water Leaks in Suburban Distribution Mains with Lift and Shift Vibro-Acoustic Sensors

Optimal Task-Space Tracking with Minimum Manipulator Reconfiguration

An Efficient Stochastic Constrained Path Planner for Redundant Manipulators

Surface Representation of Pulsed Eddy Current Sensor Signals for Improved Ferromagnetic Material Thickness Quantification

IEEE Access Special Section Editorial: Real-Time Machine Learning Applications in Mobile Robotics

Efficient Evaluation of Remaining Wall Thickness in Corroded Water Pipes Using Pulsed Eddy Current Data

Cellular Decomposition for Nonrepetitive Coverage Task with Minimum Discontinuities

Hierarchical and parameterized learning of pick-and-place manipulation from under-specified human demonstrations

Quantifying the Relative Thickness of Conductive Ferromagnetic Materials Using Detector Coil-Based Pulsed Eddy Current Sensors.

Collaborators (4)

Lili Bykerk

Arturo Gil

Ernesto Solanes

Sarath Kodagoda

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