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Funded Projects

Embodied Cognitive Robotics (ECBots)


A long-standing vision of robotics has been to create autonomous robots that can learn from the world around them and assist humans in performing a variety tasks including in our homes, in transportation settings, in healthcare as well as in dangerous situations. However, most robots today are confined to operate in carefully engineered factory settings or in applications where the amount of understanding that they need about their surroundings is fairly limited. The focus of this project is to push the state-of-the-art in uncertainty-aware active learning, self-supervised learning, and learning from interaction as well as navigation. Advancing these techniques is a strong starting point that will enable robots to continuously learn multiple tasks from what they perceive and experience by interacting with the real-world.

emss Funded by Eva Mayr-Stihl Stiftung, 2020-2022.

Brain Controlled Service Robots (ServiceBots)


In this project, the principles of interaction between the brain and novel autonomous robotic systems are being investigated. More specifically, robotic systems controlled by brain-machine interfaces are being developed to perform service tasks for paralyzed users. In this context, the focus is on the following research problems: Learning New Robotic Skills from Multimodal Brain Signal Feedback, Learning for Human-Robot Interaction, and Joint Learning of Navigation and Manipulation Tasks. As a large amount of interaction data is required for learning, an approach with several identical robots that collect and aggregate data in parallel is being exploited along with the motion capture system that provides pose information. This will enable robots to learn skills in the everyday environment within a reasonable time. More...

blbt Funded by the BrainLinks-BrainTools center of Albert-Ludwigs-Universität Freiburg, 2020-2022.

From Learning to Relearning Algorithmic Fairness for Deterring Biased Outcomes in Socially-Aware Robot Navigation (Robots4SocialGood)


Humans have the ability to learn and relearn where we adapt to physical changes in the environment, as well as adapt to mitigate actions to diminish prejudiced or inequitable conduct. We are investigating the key elements that are required to articulate both technological and social fields to mitigate socially-biased outcomes while learning socially-aware navigation strategies. With this interdisciplinary perspective, we are exploring social implications of including fairness measurements into learning techniques, considering ethical elements that pay attention to underrepresented groups of people as a support task for initiatives for inclusion and fairness in AI and robotics. This would lead to the rise of robots that positively influence society through the projection of more equitable social relationships, roles, and dynamics. More...

blbt Funded by the BrainLinks-BrainTools center of Albert-Ludwigs-Universität Freiburg, 2020-2022.

Intelligent Sensor System for Autonomous Monitoring of Production Plants in Industry 4.0 (ISA 4.0)


The ISA 4.0 project aims at developing a new mobile surveillance system for industrial plants. The goal is to support industry inspectors by taking over inspection tours and automating the inspection process. For this purpose, a mobile intelligent sensor system is being developed that depicts human senses, and analyzes the information autonomously gathered by the robot with machine learning methods. The human senses "hearing, smell, taste, sight and touch", approximately correspond to the sensing capability of microphones, gas sensors, chemical sensors, imaging systems, vibration sensors and temperature sensors. The autonomous system equipped with these sensors is intended to map and carry out inspection tours and will thereby enable an extended, improved and more objective system diagnosis. More...

bmbf Funded by the German Federal Ministry of Education and Research (BMBF), call The Federal Government's Framework Program for Research and Innovation, 2020-2022.

Open Deep Learning Toolkit for Robotics (OpenDR)


The aim of OpenDR is to develop a modular, open and non-proprietary deep learning toolkit for robotics. We will provide a set of software functions, packages and utilities to help roboticists develop and test robotic applications that incorporate deep learning. OpenDR will enable linking robotics applications to software libraries such as tensorflow and the ROS operating environment. We focus on the AI and cognition core technology in order to give robotic systems the ability to interact with people and environments by means of deep-learning methods for active perception, cognition and decisions making. OpenDR will enlarge the range of robotics applications making use of deep learning, which will be demonstrated in the applications areas of healthcare, agri-food and agile production. More...

logo1 Funded by the European Union Horizon 2020 program, call H2020-ICT-2018-2020 (Information and Communication Technologies), 2020 – 2022.

Sensor Systems for Localization of Trapped Victims in Collapsed Infrastructure (SORTIE)


The primary research objective is to improve the detection of trapped victims in collapsed infrastructure with respect to sensitivity, reliability, speed and safety of the responders. In this project, we will develop an autonomous unmanned aerial vehicle (UAV) system that can augment the process of urban search and rescue and that helps limiting the severe impacts of the disaster scenario. This will be enabled by combining sensing principles such as bioradiolocation, cellphone localization, gas detection and 3D mapping into a single unit. The seamless combination of intelligent UAVs equipped with the multi-sensor system will allow the rescue management team to quickly assess the situation in order to initiate rescue procedures as fast as possible. More...

bmbf Funded by the German Federal Ministry of Education and Research (BMBF), call International Disaster and Risk Management (IKARIM), 2020-2022.