Linear Kalman filter for dead time affected measurement signals implemented in a small scale automated guided vehicle - Lütteke, Felix; Franke, Jörg (Advances in Intelligent Systems and Computing, 2013)
This paper describes an efficient way to calculate state estimations with a linear Kalman filter, if the measurement signal is subject to a fix dead time. In addition the presented solution can handle measurement signals with arbitrarily high sample times. After the derivation of the algorithm an application with high measurement signal dead time is explained. Finally a simulation depicts the result of the algorithm being implemented on the described application. © 2013 Springer-Verlag.
CRIS-Team Scopus Importer:2023-03-07
Keywords: AGV; dead time; State estimation

Self-learning RRT* Algorithm for mobile robot motion planning in complex environments - Zhang, Xu; Lütteke, Felix; Ziegler, Christian; Franke, Jörg (Advances in Intelligent Systems and Computing, 2016)
RRT* is a practical and efficient incremental sampling-based motion planning algorithm. However, its searching ability is quite inefficient in some cases, due to relying on uniform random sampling like other RRT-based algorithms without taking the environment information and prior knowledge into account, which particularly leads to many sampling failures or generation of useless nodes in complex environments. In this paper, we propose an extension of RRT* based on a self-learning strategy and a hybrid-biased sampling scheme to improve the planning efficiency. By taking advantage of the prior knowledge accumulation and cost estimation, the searching tree has higher probability and success rate to extend in difficult areas. We also demonstrate the performance of our algorithm by building some simulation environments for our mobile robot and conclude with the results compared with RRT*.
CRIS-Team Scopus Importer:2023-03-07
Keywords: Biased sampling; Mobile robot; Motion planning; RRT*