Human-Robot Co-Evolution: Achieving the full potential of future workplaces
人机协同进化:充分发挥未来工作场所的潜力
基本信息
- 批准号:DP240100938
- 负责人:
- 金额:$ 35.21万
- 依托单位:
- 依托单位国家:澳大利亚
- 项目类别:Discovery Projects
- 财政年份:2024
- 资助国家:澳大利亚
- 起止时间:2024-01-01 至 2026-12-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Physical human-robot systems are widely used to amplify the capability of human labourers and improve ergonomics in the workplace. This project aims to develop robot controllers that shape the co-evolution of these systems. Through physical human-robot interaction studies it will generate new knowledge of how humans adapt to working with robots, which will then be incorporated into the robot controller design. Expected outcomes include a better understanding of human adaptation and a systematic approach to shaping human-robot interaction over time. This should provide significant benefits across different skill and labour-intensive industries in Australia, such as improved worker productivity and safer human-robot collaboration.
物理人类机器人系统被广泛用于增强人类劳动者的能力并改善工作场所的人体工程学。该项目旨在开发机器人控制器,以塑造这些系统的共同进化。通过物理人机交互研究,它将产生人类如何适应与机器人一起工作的新知识,然后将其纳入机器人控制器的设计中。预期成果包括更好地理解人类的适应性,以及逐步形成人机互动的系统方法。这将为澳大利亚不同的技能和劳动密集型行业带来巨大的好处,例如提高工人的生产力和更安全的人机协作。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Prof Ying Tan其他文献
Prof Ying Tan的其他文献
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{{ truncateString('Prof Ying Tan', 18)}}的其他基金
Personalised assistive robotic systems: Optimised collaborative teaming
个性化辅助机器人系统:优化协作团队
- 批准号:
DP200102402 - 财政年份:2020
- 资助金额:
$ 35.21万 - 项目类别:
Discovery Projects
Learning control and computational models of human motor systems
人类运动系统的学习控制和计算模型
- 批准号:
DP130100849 - 财政年份:2013
- 资助金额:
$ 35.21万 - 项目类别:
Discovery Projects
Real time optimisation by extremum seeking control and learning control
通过极值搜索控制和学习控制进行实时优化
- 批准号:
FT0991385 - 财政年份:2010
- 资助金额:
$ 35.21万 - 项目类别:
ARC Future Fellowships
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