从语音指令进行分层路径规划,并使用基于空间概念的拓度语义映射
Akira Taniguchi1, Shuya Ito1, Tadahiro Taniguchi1
1Emergent Systems Laboratory, Ritsumeikan University, Kusatsu, Shiga, Japan.
Frontiers in robotics and AI
|August 16, 2024
概括
这项研究介绍了一种新的机器人导航系统,该系统使用语音命令与路标来进行更灵活的路线规划. 基于空间概念的层次路径规划的拓语义映射 (SpCoTMHP) 方法提高了机器人导航的成功和速度.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 人与机器人的交互
背景情况:
- 自主移动机器人需要直观的导航来提供日常帮助.
- 当前的方法往往优先考虑最短的路径,这可能不适合用户需求.
- 灵活的路线规划与路标和实时推断对于有效的机器人辅助至关重要.
研究的目的:
- 开发一种层次空间表示和路径规划方法,使机器人能够通过路标响应语音指令.
- 使机器人能够规划改进的替代路径,适应绕道和用户指定的中间位置.
- 整合语义,拓和度量空间信息,以增强机器人导航.
主要方法:
- 提出了一种层次路径规划方法:基于空间概念的层次路径规划的拓度语义映射 (SpCoTMHP).
- 开发了一种全新的综合概率生成模型,在各层次层次上进行快速近似推断.
- 利用"控制作为概率推理"的公式来支持路径规划算法.
- 在不同的环境中使用模拟器 (SIGVerse) 和真实机器人 (丰田人类支持机器人,阿尔伯特) 进行实验.
主要成果:
- 在基线层次路径规划方法与启发式路径成本 (HPP-I) 相比,SpCoTMHP方法表现出更好的性能.
- 实现了更高的加权成功率 (0.590) 达到目标和通过正确的路线点.
- 与HPP-I相比,在高级任务中显著减少了7.14秒的计算时间.
- 成功地使用语音指令与路标来导航,例如"通过走廊进入卧室".
结论:
- 层次空间表示方便人类和机器人之间相互理解的指令.
- 该SpCoTMHP方法使自主移动机器人的基于语言的导航更加灵活和高效.
- 这种方法提高了机器人的实际应用,帮助个人进行日常活动.
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