Efficient Prediction of Human Motion for Real-Time Robotics Applications With Physics-Inspired Neural Networks

Efficient Prediction of Human Motion for Real-Time Robotics Applications With Physics-Inspired Neural Networks

Generating accurate and efficient predictions for the motion of the humans present in the scene is key to the development of effective motion planning algorithms for robots moving in promiscuous areas, where wrong planning decisions could generate safety hazard or simply make the presence of the rob...

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Bibliographic Details
Main Authors: Alessandro Antonucci, Gastone Pietro Rosati Papini, Paolo Bevilacqua, Luigi Palopoli, Daniele Fontanelli
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Human motion prediction
neural networks
social force model
service robotics
Online Access:https://ieeexplore.ieee.org/document/9663176/

Internet

https://ieeexplore.ieee.org/document/9663176/

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