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Album ds smarty fill not working4/16/2023 ![]() ![]() This paper firstly introduces the research results in the field of visual SLAM in detail through three categories: static SLAM, dynamic SLAM, and SLAM techniques combined with deep learning. MEC technology combined with 5G ultra-dense networks enables complex computational tasks in visual SLAM systems to be offloaded to edge computing servers, thus breaking the resource constraints of terminals and meeting real-time computing requirements. However, the increasing demand for computational resources by SLAM techniques limits its application on resource-constrained mobile devices. In recent years, dynamic visual SLAM techniques have been widely used in autonomous navigation, augmented reality, and virtual reality. The comprehensive overview of the SHS presented in this paper will help designers, researchers, funding agencies, and policymakers have a bird’s-eye view of the overall concept, attributes, technological aspects, and features of modern SHSs. The paper also statistically discusses the current and future research trends in the SHS, followed by a detailed portrayal of the difficulties and roadblocks in implementing them. The research then moves on to a detailed discussion of some of the important services provided by the SHS and its advantages. In addition to presenting a complete picture of the current smart home system’s (SHS) development and characteristics, this paper provides a deep insight into latest hardware and trends. The purpose of this article is to perform a systematic assessment of the latest smart home literature and to conduct a survey of research and development conducted in this field. Smart home is a habitation that has been outfitted with technological solutions that are intended to provide people with services that are suited to their needs. And the robot system has completed the task of combining independent patrol and home service well. Compared with the household service robots in the related literature, the household service robots developed by us have more complete functions. The service robot finally designed and developed realizes the functions of wireless control of home appliances, voice remote control, autonomous positioning and navigation, liquefied gas leakage alarm, and human infrared detection alarm. The indoor environment map of the home is constructed by the lidar and the attitude sensor. Arduino mega2560 is used as the bottom controller to control the movement of the service robot. ![]() ![]() When encountering a dangerous situation, the GSM module is used to give users SMS and phone alarms. The human speech is recognized by Baidu Speech Recognition API. The image information of the home is collected by the USB camera. CC2530 sets up a ZigBee network to collect home environmental information and control home electrical appliances. The system uses Raspberry Pi 3B as the main control to manage the nodes of each sensor. In response to this problem, this paper designs a smart home service robot system based on ROS. At present, the functions of home service robots are not perfect, and home service robot systems that can independently complete autonomous inspections and home services are still lacking. ![]()
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