A representation algorithm based on modified DMPs and SVD separates basic and fine-tuning shape parameters from demonstration trajectories to regenerate motion primitives with fewer adjustment parameters and achieve smooth joining for automated vehicle motion planning.
Humanlike behavior generation in urban environment based on learning-based potentials with a low-cost lane graph
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Regeneration and Joining of the Learned Motion Primitives for Automated Vehicle Motion Planning Applications
A representation algorithm based on modified DMPs and SVD separates basic and fine-tuning shape parameters from demonstration trajectories to regenerate motion primitives with fewer adjustment parameters and achieve smooth joining for automated vehicle motion planning.