Xiangda Yan, Jie Huang, Keyan He, Huajie Hong and Dasheng Xu
Robots equipped with LiDAR sensors can continuously perform efficient actions for mapping tasks to gradually build maps. However, with the complexity and scale of the environment…
Abstract
Purpose
Robots equipped with LiDAR sensors can continuously perform efficient actions for mapping tasks to gradually build maps. However, with the complexity and scale of the environment increasing, the computation cost is extremely steep. This study aims to propose a hybrid autonomous exploration method that makes full use of LiDAR data, shortens the computation time in the decision-making process and improves efficiency. The experiment proves that this method is feasible.
Design/methodology/approach
This study improves the mapping update module and proposes a full-mapping approach that fully exploits the LiDAR data. Under the same hardware configuration conditions, the scope of the mapping is expanded, and the information obtained is increased. In addition, a decision-making module based on reinforcement learning method is proposed, which can select the optimal or near-optimal perceptual action by the learned policy. The decision-making module can shorten the computation time of the decision-making process and improve the efficiency of decision-making.
Findings
The result shows that the hybrid autonomous exploration method offers good performance, which combines the learn-based policy with traditional frontier-based policy.
Originality/value
This study proposes a hybrid autonomous exploration method, which combines the learn-based policy with traditional frontier-based policy. Extensive experiment including real robots is conducted to evaluate the performance of the approach and proves that this method is feasible.
Details
Keywords
Xi Zhang, Xiangda Yan, Patricia Ordóñez de Pablos, jinghuai She, Yang Gao and Hui Chen
– This paper aims to provide clear domain knowledge and recent progresses on electronic healthcare (e-healthcare).
Abstract
Purpose
This paper aims to provide clear domain knowledge and recent progresses on electronic healthcare (e-healthcare).
Design/methodology/approach
In this paper, the authors use citation analysis to describe the trends of study on e-health with the help of CiteSpace II, a software for visualizing citation-based analysis. By analyzing the 2,752 publications and their citation data in ISI database, the authors proposed renewable figures and tables on ranking critical people, institutes, keywords and journals. Through the most influential articles given by CiteSpace, the authors can grasp the main direction in e-health researches. Furthermore, the authors analyzed the literature at e-health literacy as a case, to better understand the development of research viewpoints.
Findings
Through the analysis, the authors found that e-health is a multi-disciplinary research field and the major research about it has changed. During the early stage, health information quality on the Internet dominates. Gradually, the role of information technology (IT) becomes more important. The authors also found that some researchers, recently, have proposed the effects of IT on e-health literacy which can then improve the ability to use health information on the Internet.
Research limitations/implications
This paper has some research limitations, such as using an ISI database with most English publications. The future research may be conducted for collecting local publications data in China. It also has some implications. Based on the results, the authors claimed that IT may significantly improve people’s healthcare variance, e.g. e-health literacy. It is necessary to build new IT-based healthcare theories.
Practical implications
This paper also has some practical implications. Practitioners and institute may easily come to know which are the hot topics, top institutes and tendencies in the e-healthcare field.
Social implications
This paper may help practitioners to find common interests with other institutions and societies.
Originality/value
This paper reported the status and trend of research in this field visually, and the result will help researchers to do more in-depth research in the future.