Jonas Stenzel
Papers
9
Total Citations
80
H-Index
6
About
Jonas Stenzel is a robotics and automation researcher whose work spans human-robot interaction, autonomous navigation, and multi-robot fleet management — areas that sit at the intersection of artificial intelligence and modern industrial logistics. His most recognized contribution, a 2018 paper on safe human-robot interaction in flexible warehouses using augmented reality and heterogeneous fleet management (16 citations), introduced a pioneering safety framework enabling humans and robots to share workspaces without the traditional need for physical barriers — a significant practical advance for smart manufacturing environments. Building on this, Stenzel has made substantial contributions to deep reinforcement learning for mobile robot navigation, developing decentralized end-to-end policies that allow robots to navigate complex, dynamic environments using raw sensor data alone (14 citations). His work on automated topology creation and multi-agent path finding (MAPF) for large AGV fleets has further demonstrated his commitment to scalable, real-world deployment of robot systems in logistics. Earlier foundational work on cooperative path conflict resolution in heterogeneous robot systems (2016) established his interest in decentralized coordination. With a cumulative citation count approaching 80 across nine publications, Stenzel's research consistently bridges theoretical robotics with practical industrial application.
Research Focus
Key Achievements
Top Papers
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- 4Automated Roadmap Graph Creation and MAPF Benchmarking for Large AGV Fleets10 citations · 2022
- 5Deep Reinforcement Learning for Mobile Robot Navigation9 citations · 2019
- 6Automated topology creation for global path planning of large AGV fleets8 citations · 2021
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