With the rapid development of artificial intelligence (AI) theory, particularly deep learning
neural networks, robot vacuums equipped with AI power can automatically clean indoor …

Robot vacuum cleaners have gained widespread popularity as household appliances. One
significant challenge in enhancing their functionality is to identify and classify small indoor …

Object detection is a core capability required by sweeping robots to conduct their cleanup
jobs. Currently, deep learning-based object detection has achieved high accuracy; however …

Recently, object detection based on deep neural network has become the mainstream
research direction of sweeping robots since different obstacles may produce completely …

Numerous high-accuracy neural networks for object detection have been proposed in recent
years. Creating a specific training dataset seems to be the main obstacle in putting them into …

The intelligent operation mode decision scheme has been proved to be a promising solution
for enhancing the cleaning performance of cleaning robots. In this paper, we propose a …

Intelligence with Machine Circuit Learning Algorithms (MCLA) will become the mainstream
in complex automated robots. Its power concerns, ethical perspectives, including the issues …

Embodied intelligence based on vision-language models aims to learn from interactions and
derive general intelligence. However, existing generalized vision-language models cannot …

This paper focuses on developing modern, efficient, lightweight object detection a method
for sweeping robots while trading off parameters, FLOPs and performance. In order to …

Path planning for sweeping robots requires avoiding specific obstacles, particularly
deformable objects such as socks, ropes, faeces, and plastic bags. These objects can cause …