focus on robot ODM
Fdata's intelligent disinfection robot is named after models beginning with A1 and are available in disinfectant spray, UV disinfector, and other germicidal forms. The disinfecting robots can be used in hospitals and other public areas for autonomous extermination, reducing human contact and the risk of infection.
Common advanced robot solutions of disinfectant bots: hospitals, hotels, streets, parks, schools, squares, and mansions.
As the use of intelligent disinfection robots in industries like logistics, manufacturing, and healthcare grows, accurate navigation systems become more and more critical.
Lidar Slam and Visual Slam are two popular ways for disinfectant robots to achieve this. Lidar Slam uses Lidar sensors to create a 3D map of a robot's environment and estimate its position, while Visual Slam uses cameras to extract visual features and create a map.
The main differences are the sensors and information used to generate the map. LidarSlam is more expensive but better suited for low-light or dusty environments.
At the same time, Visual Slam is a more cost-effective solution for environments with good lighting and rich surface textures.
Both approaches provide effective solutions for different disinfectant bots applications.
Understanding these differences helps users choose the best method for their needs and get the best performance from their autonomous disinfection robot platform.
1. Intelligent obstacle avoidance. Disinfectant bots are equipped with new 360-degree omnidirectional obstacle avoidance technology, comprehensive perception of indoor dynamics + autonomous planning navigation and obstacle avoidance, SLAM, and multi-sensor fusion.
2. Intelligent disinfection. Hospital disinfection robot can realize the separation of human and machine, with a variety of disinfection modes, to meet the disinfection needs of different scenes.
3. Multi-machine collaboration. Disinfecting robots through independent research and development of communication system so that intelligent coordination to achieve AI distribution scheduling, ensure multi-robot collaboration, safety and more efficient completion of disinfection tasks.
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