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...
Main Authors: | Alessandro Antonucci, Gastone Pietro Rosati Papini, Paolo Bevilacqua, Luigi Palopoli, Daniele Fontanelli |
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Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9663176/ |
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