CLiFF-LHMP: Using Spatial Dynamics Patterns for Long- Term Human Motion Prediction
Author:
Affiliation:
1. Orebro University,AASS MRO lab,Sweden
2. Bosch Corporate Research,Robert Bosch GmbH,Stuttgart,Germany
3. School of Electrical Engineering, Aalto University,Finnish Center for Artificial Intelligence,Finland
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10341341/10341342/10342031.pdf?arnumber=10342031
Reference40 articles.
1. Human motion trajectory prediction: a survey
2. Kinodynamic motion planning on Gaussian mixture fields
3. Down the CLiFF: Flow-Aware Trajectory Planning Under Motion Pattern Uncertainty
4. Human Motion Prediction Under Social Grouping Constraints
5. Intention-based Long-Term Human Motion Anticipation
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2. Risk-aware Trajectory Prediction by Incorporating Spatio-temporal Traffic Interaction Analysis;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. LaCE-LHMP: Airflow Modelling-Inspired Long-Term Human Motion Prediction By Enhancing Laminar Characteristics in Human Flow;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
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