logo ease 2019

People master everyday tasks with ease. They manipulate objects in their environment and can deal with incomplete information (e.g. instructions) and unfamiliar circumstances (e.g. a new object or tool). The EASE Collaborative Research Center examines how robotic agents can master manipulation tasks at the competence level of humans.

The subproject H1 examines how humans flexibly adapt their sensorimotor behavior to the variety of conditions and contexts being imposed by everyday scenarios. This adaptation extends over several levels, reaching from task conditions, over object and tool properties, to on-the-fly adjustments of sensorimotor parameters. Causal relations are essential for these adaptive properties.

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Shuttle Bus aus dem Safety Control Center ProjektThe aim of the project is to establish an autonomous shuttle bus service. The vehicle will be able to pick up and drop off passengers fully autonomously at various stops along a designated route. The operation is continuously monitored and evaluated by a Safety Control Center. In the event of an unforeseen incident, the Safety Control Center can send control signals to the vehicle to resolve the situation.

Press releases:

Stadt Bremen

Universtität Bremen

SAT1 Regional

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Shuttle Bus aus dem Safety Control Center Projekt

Our project develops new approaches for automated driving in clearly defined areas and on recurring routes. The goal is to create algorithms that are not only powerful but also transferable to different environments. Together with our partners, we research and test cloud-connected methods that are practically validated in multiple test areas.

At the core are modern AI techniques such as trajectory optimization, deep learning, model predictive control, and sensor fusion. In addition, we investigate how mobile communication via 5G and satellites, V2X technologies, prediction algorithms, and remote-control concepts can make road traffic safer and more efficient.

Press releases:

City of Bremen

Universtity of Bremen

SAT1 Regional

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opa3l logo very tiny Das Projekt OPA³L - "Optimal Assistierte, hoch Automatisierte, Autonome und kooperative Fahrzeugnavigation und Lokalisation" verfolgt das Ziel, autonome Shuttle-Fahrten in bekannten Umgebungen im suburbanen Raum anzubieten. Im Projekt wird hierzu ein mit zusätzlichen Sensoren ausgerüstetes Forschungsfahrzeug genutzt. Radsensoren, GNSS, sowie ein Inertialsensor dienen zu Bestimmung des Fahrzeugzustands; LiDAR, Kamera und Radar zur Wahrnehmung der Umgebung. Der Fokus der Arbeitsgruppe Kognitive Neuroinformatik liegt auf der Fusion der vorhandenen Sensordaten, um eine robuste Schätzung des Fahrzeugzustandes sowieso der Umgebung zu erhalten, zudem auf der Routenplanung um auch bei mehreren Passagieren mit unterschiedlichen Start- und Endpunkten eine effiziente Beförderung zu gewährleisten.

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Developing a system to protect honey bees from varroa mites.

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Sensor data from bee hive is collected and analysed.

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