Adaptive State X Time Lattices A Contribution To Mobile Robot Motion Planning In Unstructured Dynamic Environments
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Adaptive State × Time Lattices: A Contribution to Mobile Robot Motion Planning in Unstructured Dynamic Environments
Author: Petereit, Janko
language: en
Publisher: KIT Scientific Publishing
Release Date: 2017-01-20
Mobile robot motion planning in unstructured dynamic environments is a challenging task. Thus, often suboptimal methods are employed which perform global path planning and local obstacle avoidance separately. This work introduces a holistic planning algorithm which is based on the concept of state.
Predictive energy-efficient motion trajectory optimization of electric vehicles
Author: Guan, Tianyi
language: en
Publisher: KIT Scientific Publishing
Release Date: 2020-01-02
Dynamic Switching State Systems for Visual Tracking
Author: Becker, Stefan
language: en
Publisher: KIT Scientific Publishing
Release Date: 2020-12-02
This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.