IA ANR-DFG-JST - Appel trilatéral ANR-DFG-JST en Intelligence Artificielle (IA)

à compléter – CHIRON

Submission summary

Dexterous manipulation of objects is a core task in robotics. Because of the design complexity needed for robot controllers even for simple manipulation task, robots currently in use are mostly limited to specific tasks within known environment. Within the CHIRON project, we aim to develop an AI empowered general purpose robotic system for dexterous manipulation of complex and unknown objects in rapidly changing, dynamic and unpredictable real-world environments. This will be achieved through intuitive embodied robotic teleoperation under optimized shared-control between the human operator enhanced with an intuitive haptic interface and the robot controller empowered with vision and learning skills. The privileged use case of such a system is assistance for “stick-to-bed” patients or elders with limited physical ability in their daily life object manipulation tasks, e.g., fetching a bottle of water and pouring it into a glass, through an intuitive and embodied robot tele-operated by themself. Such object manipulations would be otherwise not possible for them.

To make possible such an embodied tele-operated robotic system for dexterous manipulation, thus without any assumption about the object to be manipulated and the operating environment, the CHIRON project features the unique innovations simultaneously on robotics, computer vision and machine learning. Specifically, the CHIRON project will make use of a dual-arm robot and aims to bring breakthroughs in the following research topics: compliant grippers with tactile feedback, deep understanding of the scene, reinforcement learning-based shared robot control, intuitive and effective haptic interface for the embodiment of the dual-arm robot, and the last and not the least few shot learning given the very limited amount of data, e.g., trials that the envisaged system can afford with the physical ability limited human operator, for the training of the deep scene analysis and shared robot control so that the embodied dual-arm robot easily to adapt to novel operator for complex never seen before object manipulation in rapidly changing environments. As such, the CHIRON project fits perfectly the objectives of this trilateral call for proposals on AI, specifically in “advancing the state of the art in AI in order to accomplish complex tasks”; and “allowing high-level interactions with human users” and contributing in core AI technologies.

The key components required by the CHIRON project are covered with the unique symbiosis of the respective world class expertise of each partner. Prof.Hasegawa’s group from Japan brings its unique expertise in assistive robotics with embodiment for augmented human physical skills, e.g., extra robotic thumb, intelligent cane for elderly, exoskeleton. Prof. Peters’ team from Germany is providing their well known rich experience in robotc manipulation, including tactile sensing, robotic tele-operation, learning by demonstration, and reinforcement learning. Prof. Chen’s group from France is bringing their confirmed expertise in computer vision and machine learning for deep understanding of the scene for object manipulation.
The societal impact of the project is potentially huge. Instead of laying down workers when fully automating manipulation with state of the art robots, the embodied teleoperated manipulation robot system as targeted in the Chiron project is to augment general people with dexterous manipulation skills. In our privileged use case, elderly and patients, the Chiron project will enable elderly and patients to operate robots intuitively and would lead to reconstruct social welfare system to improve their independent life.

Project coordination


The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


TUD Technical University of Darmstadt

Help of the ANR 313,404 euros
Beginning and duration of the scientific project: December 2020 - 36 Months

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