Maximilian Schik — accepted AI-conference papers

2024

AutoExplorers: Autoencoder-Based Strategies for High-Entropy Exploration in Unknown Environments for Mobile Robots

Lennart Puck, Maximilian Schik, Tristan Schnell, Timothée Buettner, Arne Roennau, Rüdiger Dillmann

ICRA 2024poster

Deciding where to go next is a challenging task for humans. However, for robots in unknown environments, this becomes even more demanding. In planetary explorations, the robots are continuously challenged with the task of exploring novel areas, yet so far, humans decide for the robots where to go. E…

Cited by 0 Source ↗Scholar ↗

2022

Ensemble Based Anomaly Detection for Legged Robots to Explore Unknown Environments

Lennart Puck, Maximilian Schik, Tristan Schnell, Timothee Buettner, Arne Roennau, Rüdiger Dillmann

IROS 2022poster

Exploring unknown environments, such as caves or planetary surfaces, requires a quick understanding of the surroundings. Beforehand, only aerial footage from satellites or images from previous missions might be available. The proposed ensemble based anomaly detection framework utilizes previously ga…

Cited by 3 Source ↗Scholar ↗