DE-TGN: Uncertainty-Aware Human Motion Forecasting Using Deep Ensembles
Author:
Affiliation:
1. Civil, Structural and Environmental Engineering Department, University at Buffalo, Buffalo, NY, USA
2. Mechanical and Aerospace Engineering Department, University at Buffalo, Buffalo, NY, USA
Funder
National Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
https://ieeexplore.ieee.org/ielam/7083369/10409903/10409503-aam.pdf
Reference32 articles.
1. Uncertainty-Assisted Image-Processing for Human-Robot Close Collaboration
2. Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly
3. Dynamic Model Informed Human Motion Prediction Based on Unscented Kalman Filter
4. Recurrent Network Models for Human Dynamics
5. On Human Motion Prediction Using Recurrent Neural Networks
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1. A hybrid task-constrained motion planning for collaborative robots in intelligent remanufacturing;Mechatronics;2024-10
2. Integrating Uncertainty-Aware Human Motion Prediction Into Graph-Based Manipulator Motion Planning;IEEE/ASME Transactions on Mechatronics;2024-08
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