论文标题
人类运动和人形运动的状态估计
State Estimation for Human Motion and Humanoid Locomotion
论文作者
论文摘要
工业车间的未来见证了人类和机器人一致，而家庭家庭成为这两个代理商的共同空间的未来并不是很远。科学界通过扩展他们在人类机器人互动方面的研究工作向人类机器人合作而扩展到未来。人形机器人机器人的拟人化本质可能会认为最适合于半结构化的，以人为中心的环境中的合作。针对人类药物的可穿戴感应技术和人形机器人的有效人力意识控制策略将是实现无缝的人类人类合作的关键。在这里，可靠的州估计策略对于理解来自人类的多个分布式传感器以及机器人上的多个分布式传感器的信息至关重要，以增强为人类机器人设计的反馈控制器，以帮助其人类同行。在这种情况下，本文研究了针对人形运动和人类运动估计的谎言群体的谎言群体理论。 [持续]
The future where the industrial shop-floors witness humans and robots working in unison and the domestic households becoming a shared space for both these agents is not very far. The scientific community has been accelerating towards that future by extending their research efforts in human-robot interaction towards human-robot collaboration. It is possible that the anthropomorphic nature of the humanoid robots could deem the most suitable for such collaborations in semi-structured, human-centered environments. Wearable sensing technologies for human agents and efficient human-aware control strategies for the humanoid robot will be key in achieving a seamless human-humanoid collaboration. This is where reliable state estimation strategies become crucial in making sense of the information coming from multiple distributed sensors attached to the human and those on the robot to augment the feedback controllers designed for the humanoid robot to aid their human counterparts. In this context, this thesis investigates the theory of Lie groups for designing state estimation techniques aimed towards humanoid locomotion and human motion estimation. [continued]
