/miriam

Modular IntRalogistics Intelligent plAtforM

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Modular IntRalogistics Intelligent plAtforM

Build Status

We are aiming to revolutionize the way intralogistics are managed. Our modular platform allows the orchestration and management of thousands of AGVs. Using deep learning we learn the best rules for each vehicle in order for it to avoid other vehicles and to assign transport tasks efficiently. Additionally, the platform provides modules to support predictive maintenance through LSTM networks. The platform will be developed open source and integrated with ROS.

Publications

  • Christian Henkel The combined task allocation and path finding problem @ IROS2018 workshop (slides)

  • Christian Henkel, Jannik Abbenseth and Marc Toussaint An Optimal Algorithm to Solve the Combined Task Allocation and Path Finding Problem @ IROS2019 (more)

  • Christian Henkel and Marc Toussaint Optimized Directed Roadmap Graph for Multi-Agent Path Finding Using Stochastic Gradient Descent @ SAC2020 (more)

  • Christian Henkel, Marc Toussaint and Wolfgang Hönig GSRM: Building Roadmaps for Query-Efficient and Near-Optimal Path Planning Using a Reaction Diffusion System @ IROS2024 (more)