Real-Time Parameter Control for Trajectory Generation Using Reinforcement Learning With Zero-Shot Sim-to-Real Transfer

Real-Time Parameter Control for Trajectory Generation Using Reinforcement Learning With Zero-Shot Sim-to-Real Transfer

Research on trajectory generation algorithms for unmanned ground vehicles (UGVs) has been actively conducted due to the rapid increase in their use across various fields. Trajectory generation for UGVs requires a high level of precision, as various parameters determine the trajectory’s ef...

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Bibliographic Details
Main Authors: Chang-Hun Ji, Gyeonghun Lim, Youn-Hee Han, Sungtae Moon
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Trajectory generation
reinforcement learning
real-time parameter optimization
sim-to-real
Online Access:https://ieeexplore.ieee.org/document/10705302/
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https://ieeexplore.ieee.org/document/10705302/

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