AI empowered general purpose assistive robotiC system for dexterous object manipulation tHrough embodIed teleopeRation and shared cONtrol

人工智能赋能通用辅助机器人系统,通过具体远程操作和共享控制实现灵巧的物体操纵

基本信息

项目摘要

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 AI-based 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 unique innovations simultaneously on different AI applied domains: robotics, computer vision and machine learning.
灵巧操作物体是机器人技术的核心任务。由于机器人控制器的设计复杂性,即使是简单的操作任务,目前使用的机器人大多局限于已知环境中的特定任务。在CHIRON项目中,我们的目标是开发一个AI授权的通用机器人系统,用于在快速变化,动态和不可预测的现实世界环境中灵巧地操作复杂和未知的物体。这将通过直观的体现机器人远程操作来实现,在人类操作员与直观的触觉界面增强和机器人控制器之间进行优化共享控制,机器人控制器具有基于AI的视觉和学习技能。这种系统的特权使用情况是在日常生活对象操作任务中帮助具有有限身体能力的“坚持卧床”患者或老年人,例如,取一瓶水并将其倒入玻璃杯中,通过一个直观且具身的机器人进行远程操作。为了实现这种远程操作机器人系统的灵巧操作,无需对操作对象和操作环境进行任何假设,CHIRON项目同时在不同的人工智能应用领域进行了独特的创新:机器人技术,计算机视觉和机器学习。

项目成果

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Professor Jan Reinhard Peters, Ph.D.其他文献

Professor Jan Reinhard Peters, Ph.D.的其他文献

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{{ truncateString('Professor Jan Reinhard Peters, Ph.D.', 18)}}的其他基金

Improving the understanding of neuromuscular gait control using deep reinforcement learning
使用深度强化学习提高对神经肌肉步态控制的理解
  • 批准号:
    456562029
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants
learnINg versaTile lEgged locomotioN wiTh actIve perceptiON
学习具有主动感知的多功能腿部运动
  • 批准号:
    506123304
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Metric-based imitation learning in humans and robots
人类和机器人基于度量的模仿学习
  • 批准号:
    449154371
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Informed Exploration in Reinforcement Learning via Intuitive Physics Model Reasoning
通过直观物理模型推理进行强化学习的知情探索
  • 批准号:
    516414603
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Research Grants

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