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Diverse scenarios, precise empowerment


Whether indoors or outdoors, whether you're pursuing ultimate efficiency or absolute safety, YINTAILI Technology has the corresponding technological expertise. Explore our solutions categorized by application area and find the best path to address your specific technical challenges.

By application area

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.

RGV Shuttle: Collision Prevention for High-Speed Operation of Rail Logistics Lines

In automated production lines or automated storage systems, RGVs (rail-guided shuttle vehicles) are responsible for high-frequency, straight-line material handling tasks. Since RGVs typically carry heavy loads, operate at high speeds, and have significant braking inertia, if a person accidentally enters the vehicle’s operating path or foreign objects—such as pallet fragments or dropped cargo—fall onto the track, the vehicle will be unable to swerve and avoid the obstacle, making severe collision accidents highly likely. Traditional contact-type anti-collision barriers can only trigger at the instant of impact and cannot provide sufficient buffer distance to counteract the vehicle’s tremendous kinetic energy, thus posing an extremely high risk of equipment damage and production line downtime.

Real-time Volume Monitoring and Smart Position Closing

In the bulk material shipping process at coal mines or ports, loading efficiency directly affects the throughput of the logistics system. Traditional chute-based loading often relies on operators’ experience to perform “blind loading,” which easily leads to uneven loading (imbalanced cargo distribution), underloading (wasted space), or overloading and spillage (environmental pollution and safety hazards). If the load is uneven, vehicles are prone to tipping over during transport; if the load exceeds the vehicle’s capacity, not only does it result in costly material waste, but also exposes the operator to severe environmental and road management penalties. How to achieve “maximum filling, even distribution, and zero spillage” in a dusty environment is the core challenge in realizing unmanned loading stations.

3D Volume and Contour Detection of Fuel Vehicles for Biomass Power Plants

At biomass power plants, fuels such as straw and tree bark are typically purchased by weight. However, due to significant differences in fuel density and varying moisture content, relying solely on weighbridges can easily lead to practices like “water injection fraud” or “passing off inferior goods as superior ones” (e.g., substituting high-density, heavy materials for lighter fuels), resulting in financial losses for the power plant. Moreover, transport vehicles often carry loads that are severely non-compliant—such as excessively wide or overly tall stacks. Manual measurement not only is inefficient and prone to large data errors but also carries a high risk of damaging unloading equipment or causing safety incidents due to vehicle overloading.

Railway Foreign Object Intrusion Active Safety Monitoring

As the lifeline of the national economy, the safe operation of railways is of paramount importance. However, the complex geographical conditions along railway lines mean that risks such as rockfalls, mudslides, and intrusions by pedestrians or animals—known as "foreign-object encroachment"—constantly threaten train safety. Traditional video surveillance systems are easily affected by lighting conditions, rain, and snow, making it difficult to achieve precise, round-the-clock object detection. Meanwhile, manual inspections are inefficient and have limited coverage. Therefore, the urgent need arises to build an all-weather, blind-spot-free “invisible protective net” that can immediately sound an alarm upon the first sign of foreign-object intrusion, ensuring the safe operation of railways.

All-round low-position collision prevention and safe obstacle avoidance for unmanned forklifts

Unmanned forklifts navigate busy warehouse or factory environments, where they encounter extremely complex ground conditions. Low obstacles—such as scattered pallets and goods—as well as suddenly appearing human feet and shelf supports in narrow passageways, all pose significant safety risks to operations. Traditional single-radar solutions often suffer from “blind spots” on either side of the vehicle’s front end; particularly when the vehicle is turning, this can easily lead to lateral scrapes or collisions, resulting in machine downtime, repairs, and even injuries to personnel.

Efficient, seamless passage through ETC lanes

Addressing the pain points of traditional inductive loop sensors used in ETC lanes—such as road disruption during construction, difficult maintenance, high failure rates, susceptibility to interference leading to missed vehicle detections, and limited functionality that cannot be upgraded—along with the core requirements of “non-destructive installation, precise detection, stable operation and maintenance, and scalable functionality”—the ETC laser coil offers an upgrade solution.

Intelligent Intrusion Prevention System for Platform End Zones

The ends of platform platforms connect to the train operating sections and are high-risk areas where passengers are strictly prohibited from entering. However, some passengers, due to a lack of safety awareness or while making phone calls, often inadvertently step over the safety yellow line or even enter the restricted end zones. This not only puts them at significant personal safety risks but can also force trains to stop abruptly, severely disrupting railway transportation order. Traditional methods of physical barriers or manual intervention suffer from issues such as large coverage blind spots, delayed response times, and high labor costs, making it difficult to achieve effective, round-the-clock monitoring and control.

Railway Crossing Hazard Area Availability Notice

Railway level crossings are high-risk areas for off-track safety incidents, where dangerous situations such as pedestrians and vehicles rushing across the tracks and vehicle breakdowns causing delays occur frequently. The traditional “guard + barrier mechanism” model struggles to completely prevent unauthorized intrusions. Meanwhile, video-based monitoring systems are highly susceptible to interference from strong sunlight, nighttime conditions, and rain or fog, leading to detection blind spots and delays. Once an object encroaches onto the track, if the system fails to accurately detect it and issue an alarm within seconds, high-speed trains often won't have enough time to brake, greatly increasing the risk of serious accidents.
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