no code implementations • 8 Apr 2024 • Ahmed Faisal Abdelrahman, Matias Valdenegro-Toro, Maren Bennewitz, Paul G. Plöger
To investigate the utility of brain-inspired sensing and data processing, we developed a neuromorphic approach to obstacle avoidance on a camera-equipped manipulator.
1 code implementation • 25 Mar 2024 • Sicong Pan, Liren Jin, Xuying Huang, Cyrill Stachniss, Marija Popović, Maren Bennewitz
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment.
no code implementations • 27 Sep 2023 • Arindam Roychoudhury, Shahram Khorshidi, Subham Agrawal, Maren Bennewitz
Three main areas of application are identified, namely, internal state estimation, external environment estimation, and human robot interaction.
no code implementations • 4 Oct 2022 • Murad Dawood, Nils Dengler, Jorge de Heuvel, Maren Bennewitz
Our experiments show that MPC as an experience source improves the agent's learning process for a given task in the case of sparse rewards.
no code implementations • 30 Sep 2022 • Rohit Menon, Tobias Zaenker, Nils Dengler, Maren Bennewitz
Active perception for fruit mapping and harvesting is a difficult task since occlusions occur frequently and the location as well as size of fruits change over time.
no code implementations • 28 Mar 2022 • Jorge de Heuvel, Nathan Corral, Lilli Bruckschen, Maren Bennewitz
For the most comfortable, human-aware robot navigation, subjective user preferences need to be taken into account.
no code implementations • 3 Feb 2021 • Christopher Gebauer, Maren Bennewitz
In a second stage, we show the usage of the compact state representation generated by our autoencoding pipeline in a simplistic navigation task and expose the pitfall that increased reconstruction power will always lead to an improved performance.
no code implementations • 9 Jul 2020 • Jonas D. Hasbach, Maren Bennewitz
Human-swarm interaction (HSI) is an active research challenge in the realms of swarm robotics and human-factors engineering.
no code implementations • 13 Dec 2019 • Julian Tanke, Oh-Hun Kwon, Patrick Stotko, Radu Alexandru Rosu, Michael Weinmann, Hassan Errami, Sven Behnke, Maren Bennewitz, Reinhard Klein, Andreas Weber, Angela Yao, Juergen Gall
The key prerequisite for accessing the huge potential of current machine learning techniques is the availability of large databases that capture the complex relations of interest.