Recently, with the in-depth development of Industry 4.0 worldwide, mobile robots have
become a research hotspot. Indoor localization has become a key component in many fields …

This paper proposes a novel incremental training mode to address the problem of Deep
Reinforcement Learning (DRL) based path planning for a mobile robot. Firstly, we evaluate …

Currently there is no standard indoor positioning system, similar to outdoor GPS. However,
WiFi signals have been used in a large number of proposals to achieve the above …

One of the most popular approaches for indoor positioning is WiFi fingerprinting, which has
been intrinsically tackled as a traditional machine learning problem since the beginning, to …

WiFi is widely used for indoor positioning because of its advantages such as long
transmission distance and ease of use indoors. To improve the accuracy and robustness of …

The ability to identify objects of interest from digital visual signals is critical for many
applications of intelligent systems. For such object detection task, accuracy and …

In the intelligent logistics and warehouses, the autonomous mobile device (AMD) holds a
key position as it is equipped with the ability to carry out functions like material transportation …

When a traditional Deep Deterministic Policy Gradient (DDPG) algorithm is used in mobile
robot path planning, due to the limited observable environment of mobile robots, the training …

Recent studies have demonstrated the success of using the channel state information (CSI)
from the WiFi signal to analyze human activities in a fixed and well-controlled environment …

Time series analysis is essential to many far-reaching applications of data science and
statistics including economic and financial forecasting, surveillance, and automated …