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Endowing mobile robots with exceptional perceptual capabilities
We offer a full range of LiDAR solutions—from 2D to 3D, covering everything from navigation and obstacle avoidance to safety protection—serving as the core engine for building efficient, intelligent mobile robotic systems.
Mobile robot
In-Ground Vehicle (IGV): All-Weather, Outdoor 3D Obstacle Avoidance and Environmental Perception
Port terminals are typical all-weather, unstructured outdoor environments. When operating, unmanned ground vehicles (IGVs/ARTs) face complex lighting challenges: intense glare at noon, low illumination at night, and reflections from waterlogged surfaces—all of which can severely interfere with the visual cameras’ ability to make accurate judgments. Moreover, terminal surfaces often littered with low, small objects such as container locks, maintenance tools, or traffic cones—traditional single-line LiDAR systems are highly prone to “missing” these objects when scanning from above, potentially leading to vehicle tires being punctured or damaged by running over such objects, thereby impacting port operational efficiency.
Autonomous Sweeper: Edge-Adaptive Cleaning Guidance and Ground Obstacle Detection
Unmanned cleaning vehicles primarily operate in outdoor settings such as parks, plazas, or sidewalks. To ensure comprehensive cleaning coverage, these vehicles typically perform “edge-cleaning”—that is, they drive closely alongside curbs. This task places extremely high demands on perception accuracy: the vehicle must not only identify the exact position of the curb to maintain its course but also prevent its wheels from scraping against the curb. Moreover, outdoor environments feature dramatic changes in lighting conditions—such as shade from trees and intense sunlight—and often include low stone pillars, steps (negative obstacles), or non-rigid debris like piles of fallen leaves. As a result, conventional sensors struggle to reliably distinguish between “debris that can be safely traversed” and “obstacles that must be avoided.”
Autonomous Forklift: Lateral Clearance Monitoring and Collision Avoidance in Narrow Aisles
In automated stereoscopic warehouses pursuing high-density storage, rack aisles are typically designed to be extremely narrow (VNA). When unmanned forklifts travel at high speeds within these aisles, even a slight deviation or an unexpected protrusion of goods from the racks into the aisle can easily lead to accidents such as goods scraping against racks or the forklift becoming stuck. Traditional single-point ranging sensors can only detect fixed points and cannot cover the entire three-dimensional space along the sides, making it difficult to identify irregularly protruding obstacles.
In automated warehouses with dense storage, AGVs and AMRs need to swiftly navigate through narrow aisleways between shelves. Traditional 2D LiDAR sensors can only scan a single plane at a fixed height above the ground—typically around 20 cm—leaving significant vertical blind spots. As a result, low obstacles on the ground—such as dropped delivery boxes or abandoned pallet blocks—or suspended objects just slightly above the ground—such as pallet corners extending from the bottom of shelves—often go completely unnoticed by 2D LiDAR. This makes robots highly susceptible to undercarriage scrapes, cargo collisions, or even impacts against shelf uprights, potentially leading to serious safety incidents.
Autonomous Forklift: 3D Obstacle Avoidance and Spatial Safety Protection
When operating among densely packed storage racks, unmanned forklifts face complex three-dimensional spatial challenges. Traditional 2D obstacle-detection radars can only scan a plane approximately 20 cm above the ground, leaving a significant vertical blind zone. As a result, these radars often “fail to see” overhead rack beams, partially protruding goods, or low-level pallets on the floor. This makes forklifts highly susceptible to accidents during operation—such as collisions between the mast and overhead objects or damage to goods from rubbing against surrounding facilities. Such incidents not only cause costly damage to logistics equipment but also pose a serious threat to the safety of personnel on site.
Autonomous Navigation and Obstacle Avoidance for Intelligent Warehouse Mobile Robots (AGVAMR)
In modern e-commerce warehouses or flexible manufacturing workshops, logistics paths are complex and ever-changing. Traditional navigation methods using magnetic strips or QR codes are cumbersome to implement and offer rigid routes, making them no longer suitable for the demands of “flexible production.” The next-generation mobile robots need to be equipped with SLAM-based natural navigation capabilities—enabling them to autonomously localize themselves and plan paths in environments without any auxiliary markers. Meanwhile, given the mixed human-robot flow within warehouses and the dynamic nature of goods placement, robots must possess highly sensitive, autonomous obstacle-avoidance capabilities to prevent collisions with shelves or personnel and ensure continuous, efficient operations.
Flexible Obstacle Avoidance and Area Safety Protection for Mobile Robots (AGV/AMR)
At e-commerce sorting or material-handling sites, a large number of recessed AGVs need to swiftly navigate through narrow aisleways between shelves, and human-machine mixed-mode operations have become the norm. Traditional mechanical bumpers can only trigger after a collision has already occurred—acting as a “post-event remedy”—and thus cannot prevent collision-related damage. Meanwhile, conventional infrared sensors have a short detection range and are heavily affected by light interference, making it difficult for them to detect personnel wearing dark-colored clothing or black obstacles. Moreover, when AGVs turn in narrow aisles, their fixed-shaped detection zones tend to easily scan the shelf uprights on either side, leading to frequent false alarms and unnecessary stops, which severely impacts logistics efficiency.
Autonomous Forklift: Autonomous Positioning, Navigation, and Operational Safety Protection
In automated warehousing and logistics, unmanned forklifts often need to operate in narrow aisleways between shelves and in busy transfer zones. Traditional laser reflector-based navigation requires installing numerous reflectors on walls and shelves, a process that is both labor-intensive and costly to maintain. Moreover, if the positions of shelves are changed, the navigation system must be reconfigured from scratch. Additionally, forklifts are heavy and have significant inertia; if they fail to promptly detect suddenly appearing personnel or scattered goods while moving, they can easily cause serious safety incidents or even lead to shelf collapses.
Commercial Service Robots: Autonomous Navigation and Human-Robot Interaction Safety
In commercial settings such as hotels, office buildings, or hospitals, service robots need to autonomously navigate through crowded corridors and lobbies with ever-changing environments. Traditional magnetic-strip navigation systems disrupt interior design aesthetics and are therefore prohibited; meanwhile, visual navigation is easily affected by changes in lighting conditions. Moreover, commercial environments are often characterized by glass curtain walls, marble floors (high reflectivity), and dark-colored carpets (high light absorption), and may at any time be populated by running children or temporarily placed luggage. Robots not only have to achieve precise trackless navigation but also must possess highly sensitive obstacle-avoidance capabilities to ensure absolute safety when interacting closely with people—while simultaneously maintaining a slim and aesthetically pleasing body design.
Safety Protection for Mobile Operations of Synthetic Fiber Winding Machines
In the synthetic fiber textile workshop, automatic bobbin-replacement carts need to frequently shuttle back and forth between the long winding machine aisles, performing the heavy-duty task of changing bobbins. The aisles are narrow, and often populated by inspectors or temporarily parked trolleys. Once a bobbin-replacement cart collides with personnel while moving, it not only could cause injuries to workers but also might damage the precision winding machines—and even bring down the entire production line, resulting in substantial losses. Traditional mechanical anti-collision strips are slow to react and cannot provide non-contact, proactive safety protection.
Integrated Autonomous Navigation, Positioning, and Safe Obstacle Avoidance for AGVs
For AGVs and AMRs that employ laser SLAM navigation technology, the key to design lies in how to simultaneously address two core challenges—“Where am I?” and “What’s ahead?”—within the constraints of limited vehicle space and a tight cost budget. Deploying separate navigation radar and obstacle-detection radar not only increases hardware costs but also consumes valuable installation space and complicates system integration. The market urgently calls for a “multi-purpose” sensor solution that can both provide high-precision environmental contour data for mapping and localization and independently deliver reliable safety protection.
Photovoltaic Wafer Handling AGV: High-Precision Navigation and Three-Dimensional Safety Protection
In the intelligent production workshop for photovoltaic cells, AGVs are responsible for handling the high-value, highly fragile silicon wafer baskets. Due to the compact nature of the workshop environment, machinery often features suspended displays or operating consoles, and AGVs themselves tend to be relatively tall—typically standing over 1.5 meters in height. If radar sensors were installed only at the bottom of the AGV, this would create a significant “upper-body blind zone.” Should an AGV’s upper body collide with anything, not only could expensive production equipment be damaged, but the intense vibrations could also cause the entire stack of silicon wafers to shatter, resulting in severe economic losses. Moreover, AGVs must precisely dock with machine conveyor belts to within millimeter-level accuracy, placing extremely stringent demands on navigation precision.
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Corporate email:
kf@yintaili.cn
Beijing Headquarters Address:
Building 3, Zone 3, Yongfeng Technology Enterprise Accelerator, Haidian District, Beijing Municipality, 2nd Floor
North China Operations Center:
Building 5B, Jindi Weixin·Yongtai Intelligent Manufacturing Park, Anfu Road, Xiqing District, Tianjin City
Henan Branch:
Unit 902, Building 1, Xinyuan International Plaza, Jianshe Road Subdistrict, Zhongyuan District, Zhengzhou City, Henan Province
Jiangsu Branch:
Room 605B, Building A, Anke Building, Jianye District, Nanjing City, Jiangsu Province
