no code implementations • 28 Jul 2023 • Matthias Brucker, Andrei Cramariuc, Cornelius von Einem, Roland Siegwart, Cesar Cadena
We evaluate our method on a custom dataset featuring railway images with artificially augmented obstacles.
1 code implementation • 27 Jul 2020 • Zhenshan Bing, Matthias Brucker, Fabrice O. Morin, Kai Huang, Alois Knoll
In this paper, we propose graph-based hindsight goal generation (G-HGG), an extension of HGG selecting hindsight goals based on shortest distances in an obstacle-avoiding graph, which is a discrete representation of the environment.