给定性等级是机器人任务指令的理论序列
Zhao Han1, Daniel Hammer1, Kevin Spevak1
1Department of Computer Science, Colorado School of Mines, Golden, CO, United States.
Frontiers in robotics and AI
|October 10, 2025
概括
机器人可以通过使用Giveness Hierarchy (GH) 来规划对象引用来提高任务指令. 这使得人类更容易理解和高效地完成机器人教导的任务.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人与机器人的交互
- 认知科学 认知科学
背景情况:
- 协作机器人教人类新任务需要精心排序指令.
- 机器人任务指令的定位和动态性质带来了独特的挑战.
研究的目的:
- 调查机器人如何利用Giveness Hierarchy (GH) 来规划对象引用.
- 为人类队友生成连贯且易于遵循的指令.
主要方法:
- 使用了Giveness Hierarchy (GH) 作为一个规划框架.
- 开发了一个基于GH的计划器,用于在机器人指令中对象引用的序列化.
主要成果:
- 机器人生成的指令被评为更自然,流,易懂和智能.
- 指令导致人类参与者的工作负担减少.
- 任务完成效率得到了提高.
结论:
- 利用Giveness Hierarchy (GH) 提高了机器人的指令生成.
- 基于GH的规划可以在任务学习中实现更有效的人机协作.
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