智能家居环境中基于移动机器人的失物搜索

王祺; 樊臻; 盛卫华; 张森林; 刘妹琴

doi:10.1631/FITEE.1800275

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智能家居环境中基于移动机器人的失物搜索

常规文章 | Updated：2022-05-19

- 智能家居环境中基于移动机器人的失物搜索
- Finding misplaced items using a mobile robot in a smart home environment
- 信息与电子工程前沿（英文） 2019年20卷第8期页码：1036-1048
- Affiliations：
  
  College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
  School of Electrical and Computer Engineering, Oklahoma State University, Stillwater OK 74078, USA
- Author bio：
  
  Mei-qin LIU, E-mail: liumeiqin@zju.edu.cn
- Funds：
  
  Project supported by the Basic Public Research Program of Zhejiang Province, China (No. LGF18F030001) and the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT1800414)
- DOI：10.1631/FITEE.1800275
  中图分类号： TP242.6
- 收稿：2018-05-03，
  
  修回：2019-;8-;9，
  
  纸质出版：2019-08
- Accepted：
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王祺, 樊臻, 盛卫华, 等. 智能家居环境中基于移动机器人的失物搜索[J]. 信息与电子工程前沿（英文）, 2019,20(8):1036-1048.

Qi WANG, Zhen FAN, Wei-hua SHENG, et al. Finding misplaced items using a mobile robot in a smart home environment[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(8): 1036-1048.
王祺, 樊臻, 盛卫华, 等. 智能家居环境中基于移动机器人的失物搜索[J]. 信息与电子工程前沿（英文）, 2019,20(8):1036-1048. DOI： 10.1631/FITEE.1800275.

Qi WANG, Zhen FAN, Wei-hua SHENG, et al. Finding misplaced items using a mobile robot in a smart home environment[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(8): 1036-1048. DOI： 10.1631/FITEE.1800275.

摘要

智能家居可提供补充信息以帮助家居服务机器人。本文利用智能家居环境中机器人所获取的历史轨迹数据，提出一种机器人失物搜索（MIF）系统。首先，提出一种多传感器融合方法定位和跟踪用户。其次，利用人物历史轨迹所包含的知识，提出一种路径规划方法生成机器人搜索路径。再次，应用一种基于卷积神经网络的实时物体检测单元检测目标丢失物品。基于搭建的智能家居测试平台进行MIF系统相关实验。最后，实验结果验证了所提方案的准确性和有效性。

Abstract

Smart homes can provide complementary information to assist home service robots. We present a robotic misplaced item finding (MIF) system

which uses human historical trajectory data obtained in a smart home environment. First

a multi-sensor fusion method is developed to localize and track a resident. Second

a path-planning method is developed to generate the robot movement plan

which considers the knowledge of the human historical trajectory. Third

a real-time object detector based on a convolutional neural network is applied to detect the misplaced item. We present MIF experiments in a smart home testbed and the experimental results verify the accuracy and efficiency of our solution.

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Cloud-assisted cognition adaptation for service robots in changing home environments