Nico Michel | AI LAB @ UniBw Munich

AUSPEX @ GAS 2025

Thu, 11 Dec 2025 00:00:00 +0000

At the German Autonomy Summit (GAS) 2025, held by the IEEE Intelligent Transportation Systems Society (ITSS) German Chapter, Maximilian Schnell and Nico Michel presented their teams research “AUSPEX: An Integrated Open-Source Decision-Making Framework for UAVs in Rescue Missions”. The event brought together Germanys leading researchers of intelligent transportation systems, with a focus on autonomous systems and perception of mobile systems. The summit fostered engaging discussions and offered valuable feedback from peers working at the forefront of perception, navigation, control, learning and autonomous systems.

Nico Michel

Thu, 11 Dec 2025 00:00:00 +0000

Nico Michel completed his Bachelor’s Degree in Mechanical Engineering at the Technical University of Munich in 2019 with a focus on Nonlinear Flight Control. In 2020, he continued his studies with a Master’s in Mechatronics and Robotics at TUM, during which he focused on Robotics and Control Systems. He accomplished his Master’s degree with his Master’s thesis on Map-Based Navigation with Semantic Segmented Aerial Images. Nico gained research experience as a member of TUM: Junge Akademie, a scholarship program for talented young scientists. Further, he spent two semesters abroad at McGill University in Montreal, Canada, and at the University of Technology in Sydney, Australia. His research interests focus on GNSS-denied navigation for decentralized intelligent systems.

Project MENTHON: Workshop at the UniBW

Fri, 31 Oct 2025 00:00:00 +0000

As part of the MENTHON project, a joint demonstration took place on October 31, 2025 together with our partners AID and HAT.tec. We were pleased to welcome representatives from the VDI project management agency as well as associated partners from the DGzRS and the Bergwacht Penzberg.

During the event, we showcased the capabilities of the AUSPEX framework in realistic search and rescue scenarios. One scenario demonstrated how a missing person was located by a heterogeneous drone swarm, identified using advanced object detection, and subsequently supported by a second drone that delivered a first-aid kit directly to the position.

In addition to the live demonstrations, technical presentations were held and further real-world mission scenarios were discussed. The day concluded with a joint dinner for all participants. The deployed drone swarm consisted of an MK-20 multicopter (ArduPilot) equipped with a zoom and thermal camera, as well as two Holybro X500 v2 (PX4) drones – one carrying a camera and the other transporting a first-aid kit.