Quality slam scanner factory: SLAM100 is the first handheld mobile lidar scanner launched by Feima Robotics. Thesystem has a 360° rotating head, which can form a 270°x360° point cloud coverage.Combined with the industry-level SLAM algorithm, it can obtain high-precision three.dimensional point cloud data of the surrounding environment without light and GPS. SLAM200 is the third generation high-precision handheld laser scanner. SLAM200 LiDAR Scanner features a panoramic camera, a higher-performance laser sensor, built-in GNSS module and a more powerful processing unit, offering higher precision, finer details, and more convenient functions. SLAM200 handheld Lidar Scanner is a more efficient and convenient measurement tool to obtain high-precision 3D point cloud data of the surrounding environment. See additional details on robot joint motor.
Our Automatic Robot line includes Robot Chassis, Following Robots, and Integrated Joints. These robots are equipped with autonomous navigation systems and high-precision mechanical joints, perfect for industrial automation, smart logistics, warehouse management, and research. For example, our Following Robots feature high load capacity and are designed to autonomously follow operators in warehouses and factories, easing material transport. Additionally, our intelligent robotic joints offer unmatched precision and flexibility for robotic arms and collaborative robots. Complementing these systems are our video transmission modules, data links, and wireless control systems for optimal performance across various scenarios.
Heritage Building Scanning in Ximen Old Street, Yiwu, Zhejiang (Handheld + Aerial Mode) – According to user requirements, a historical building was scanned using both aerial and handheld modes, resulting in a complete dataset of the heritage structure. Highway Bridge Facade Scanning in Zhejiang (Aerial Mode Only) – Data collection focused on evaluating bridge navigability. The measured area included both facades of a 1400-meter bridge section. Manual drone flights enabled full-scope scanning in a single mission, significantly improving efficiency. The data showed elevation accuracy better than 5 cm, supporting accurate navigability assessments.
Let’s look at how companies are actually using handheld lidar scanners to improve their operations. These stories show how lidar can make a tangible difference in various industries. Imagine a large-scale construction project. Using handheld lidar, the project managers can track progress daily, identifying any deviations from the plan immediately. This allows them to address issues proactively, preventing costly delays. Or consider a film production company using lidar to create realistic 3D models of locations for special effects. This saves time and money compared to traditional methods. Here are a few more examples: Archaeology: Researchers use lidar to map ancient sites and uncover hidden structures, providing valuable insights into past civilizations. Mining: Companies use lidar to monitor stockpile volumes, optimize blasting operations, and improve mine safety. Real Estate: Agents use lidar to create immersive virtual tours of properties, giving potential buyers a realistic view from anywhere in the world. Forensics: Investigators use lidar to document crime scenes quickly and accurately, capturing every detail for analysis. Find more details on https://www.foxtechrobotics.com/.
Since the start of the year, the global competition in humanoid robotics has intensified. Videos showcasing robots dancing, flipping, and running have flooded social media, captivating audiences worldwide. While these feats highlight impressive technological breakthroughs, the true value of humanoid robots lies beyond entertainment. The Global Boom in Humanoid Robotics – Some argue that robots are now living the ideal lives of humans—dancing and running while we remain at work. However, the real question is: how close are we to seeing these robots solving practical challenges in industries?
Technology Breakthrough: How Handheld SLAM Devices Solve These Challenges – Open-pit mines are vast. Static scanning requires repeated setup, which slows down data collection and makes large-scale modeling inefficient. High labor costs: Traditional methods require team coordination and involve cumbersome workflows prone to human error. Poor adaptability to dynamic scenes: Mining operations are highly dynamic. Activities such as blasting, excavation, and support frequently change the terrain. Static survey results become outdated quickly, limiting their usefulness in real-time decision-making. Geological disasters, like collapses or landslides, demand rapid post-event mapping to assess the site quickly and accurately.