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Flexible human-robot cooperation with shared task representation (FlexCobot)

Flexible human-robot cooperation with shared task representation (FlexCobot)
具有共享任务表示的灵活人机合作 (FlexCobot)
批准号:
397804710
负责人:
Professor Dr. Dominik Henrich
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2017
资助国家:
德国
项目状态:
已结题
起止时间:
2016-12-31 至 2022-12-31

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中文摘要
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英文摘要
In traditional automation systems, robots are used to repeatedly perform the same task for a long period of time. Fences often ensure the safety of human workers by preventing them from entering the robot workspace. Recent advances enable safe human-robot coexistence without these physical barriers. With humans and robots being able to move safely within the shared workspace, it is possible to integrate human agents into the production process. Humans and robots can work on a common goal using their individual skills. With this symbiotic combination of intelligent robotics and the cognitive skills that are unique to humans, hybrid and flexible cooperating systems can be de-signed that are useful for many applications, such as small-series production, service, workshops, laboratories and households. The goal of the research project “FlexCobot” is to develop and investigate new concepts for flexible human-robot cooperation. Given to the robot system is a human and a machine-readable representation of the task, which is composed of elementary operations. The task shall be fulfilled by a team of humans and robots as correctly, quickly, and conveniently as possible. As basis a paradigm is followed, which considers all agents as equal partners such that each elementary operation can be carried out by each agent. Based on this paradigm, flexibility regarding the team composition, the tasks to be undertaken, and the objects is sought for human-robot cooperation. Using a prototypical realization, central questions to be answered are: What is an appropriate shared object representation, an efficient co-ordination, and a system architecture for one or more robots?
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Semantic and Local Computer Vision based on Color/Depth Cameras in Robotics (SeLaVi)
Verbal instructing of sensor-based robots (VerbBot)
Online CAD reconstruction with hand-held depth cameras (HandCAD-2)
Intuitive programming of robot manipulators (INTROP)
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