Transport Robot

Description

Autonomous Forklift is a specialized form of intelligent transport vehicle (AGV/AMR), capable of autonomous positioning and path planning by integrating technologies such as LiDAR, visual recognition, SLAM navigation, and AI algorithms. It can perform automated material transportation in scenarios involving heavy loads, high lifting, storage/retrieval, and complex stacking tasks.

Combining the mechanical capabilities of traditional forklifts with autonomous driving technology, it is primarily used in Warehousing and Logistics (Automated high-rise warehouses, e-commerce sorting centers),Manufacturing Industry (In-plant logistics for automotive, home appliance production lines), Ports and Terminals (Container transport), Cold Chain and Hazardous Environments (Cold storage facilities, chemical plants) etc.

It effectively addresses key challenges of manual handling, including low efficiency, high safety risks, and intense labor demands for heavy-load operations, significantly improving automation and operational efficiency.

Transport Robot

Why Choose Autonomous Forklifts?

1. 24/7 Operation, Autonomous forklifts can operate continuously for 7×24 hours without the need for breaks or shift changes, making them ideal for high-intensity environments such as warehousing, logistics, and manufacturing. In contrast, traditional forklifts are limited by human working hours, average daily operation time of only 8–10 hours.

2. Precision Handling, Equipped with LiDAR, vision recognition, and servo control systems, autonomous forklifts achieve millimeter-level positioning accuracy (e.g., lifting error <5mm). stacking neatness improves by over 90%, compared to manual operations, where fatigue often leads to misalignment or damage of goods.

3. Dynamic Safety Protection and Accident Avoidance, Over 30% of logistics accidents involve traditional forklifts, primarily due to speeding, blind spots during reversing, or unauthorized personnel entering hazardous zones. In contrast, autonomous forklifts integrate a multi-sensor fusion system, including LiDAR, cameras and ultrasonic sensors, that continuously scans the environment. They can dynamically detect pedestrians and obstacles, and trigger emergency braking within 0.1 seconds , bringing the accident rate close to zero.

4. Extreme Environment Adaptability, Autonomous forklifts are equipped with low-temperature-resistant batteries that enable stable operation in cold storage environments as low as -30°C , and feature explosion-proof designs suitable for hazardous areas like chemical plants. Traditional forklifts require workers to wear protective gear when operating in extreme conditions such as cold storage, high temperatures, or dangerous material zones, resulting in lower efficiency and higher risk.

5. Cost Control and ROI Optimization, Traditional forklift operations incur ongoing costs such as driver salaries, training, and social insurance, and are increasingly affected by labor shortages. But each autonomous forklift can replace 2–3 human operators , reducing labor costs by 50–70% . Moreover, the initial investment can typically be recouped through improved efficiency within 1–3 years , offering strong economic returns.

Core Functional Requirements

Autonomous Navigation and Positioning Technology

LiDAR with SLAM Algorithm: Uses LiDAR to scan the surrounding environment and combines it with Simultaneous Localization and Mapping (SLAM) technology to build dynamic maps in real time and determine its own position. This allows the robot to operate without relying on fixed navigation markers (such as magnetic strips or QR codes), making it suitable for complex environments like mixed-traffic warehouses.

Vision-Based Navigation: Utilizes cameras to recognize ground textures, shelf labels, or QR codes, and applies deep learning algorithms for high-precision path planning.

GPS/Beidou + Inertial Navigation: Supports seamless switching between outdoor GPS/Beidou positioning and indoor laser/vision-based navigation. In outdoor scenarios, satellite positioning is combined with gyroscopes and accelerometers to achieve large-scale localization (such as container handling at ports).

Multi-source fusion positioning: Fusion of laser, visual, GPS, and other data to improve positioning robustness (e.g., stable operation even in changing light conditions or obstructed scenes).

Multi-Sensor Fusion and Obstacle Avoidance

LiDAR: Performs 360° scanning to detect surrounding obstacles (such as pedestrians, shelves, and other vehicles), with ranging accuracy down to the millimeter level.

Cameras and Computer Vision: Identifies object shapes, shelf numbers, and traffic signs, and can even analyze human behavior (such as predicting sudden pedestrian intrusions into the robot’s path).

Ultrasonic and Infrared Sensors: Detects low-profile or ground-level obstacles at close range (such as scattered items, bumps, or depressions on the floor).

Dynamic Obstacle Avoidance Algorithms: Based on real-time perception data, the system rapidly generates alternative routes to avoid collisions (for example, automatically decelerating or rerouting when encountering a suddenly stopped vehicle),ensuring safe and smooth operation in dynamic environments.

Motion Control and Execution Technology

High-precision servo control: Millimeter-level precision control of forklift lifting, tilting, and steering is achieved through servo motors and hydraulic systems, ensuring stable cargo transport (such as anti-shaking algorithms when handling fragile items).

Multi-DOF (Degrees of Freedom) Mechanical Design: Allows the fork arms to automatically adjust in width, height, and angle to accommodate various pallet sizes and types (For example, combined with visual recognition, the system can precisely align with pallet positions for efficient and reliable loading/unloading).

Optimized Power System: Equipped with a lithium battery and intelligent energy management system, supporting fast charging and automatic charging docking. Provides 8–12 hours of continuous operation , making it ideal for high-intensity logistics tasks in industrial and warehousing environments.

Safety and Human-Machine Interaction Technologies

Emergency braking system: One-button power cut-off or mechanical braking in case of emergency.

360° Anti-Collision Zone: Sensors define a safety zone around the robot. When an obstacle or person enters this area, the robot automatically slows down or stop to avoid collision.

Audio-Visual Warnings: Equipped with warning lights and voice alerts that activate during operation to notify nearby personnel and ensure safe distancing.

Human-machine interface (HMI): Touch screen or remote monitoring system displays task status and fault diagnosis information, and supports manual intervention control (such as emergency takeover).

System Integration and Scheduling Technology

Task Scheduling System (Fleet Management System, FMS): When multiple autonomous forklifts work together, tasks are assigned and routes optimized through a central system to avoid congestion (e.g., dynamically adjusting routes based on real-time traffic flow).

Integration with Enterprise Systems: Seamlessly connects with WMS (Warehouse Management System) , ERP (Enterprise Resource Planning) , and MES (Manufacturing Execution System) to enable order-driven automated material transportation. For instance, upon receiving an instruction from WMS, the robot can autonomously navigate to the designated shelf to retrieve or deliver goods—enhancing end-to-end logistics automation and operational efficiency.

Advantages

Automated Operation: Through sensors (LiDAR, cameras, and ultrasonic modules), positioning systems (GPS and SLAM) and AI algorithms, these robots can achieve autonomous navigation, intelligent path planning, and dynamic obstacle avoidance—completely eliminating the need for manual operation.

24/7 Continuous Operation: Autonomous forklifts avoid issues associated with human labor such as rest breaks, shift changes, and fatigue. This makes them ideal for high-intensity environments like warehouses and manufacturing plants.

High load capacity: Typically with a load range of 1-10 tons and a lifting height of up to several meters (e.g., 4-6 meters), suitable for handling pallets, containers, and large parts.

Comprehensive Safety Protection: Integrated with multi-layer safety mechanisms, including Emergency stop function, 360° anti-collision sensors, Infrared detection, Audio-visual warning alerts, Ensuring safe interaction with personnel and surrounding infrastructure.

Dynamic Obstacle Avoidance: Continuously detects pedestrians, vehicles, and unexpected obstacles in real time, automatically adjusting routes or stop when necessary.

Integration with Warehouse Systems: Supports connectivity with WMS (Warehouse Management System) and ERP (Enterprise Resource Planning), Enabling automated task dispatching, real-time inventory synchronization, and intelligent logistics management—facilitating end-to-end digitalization and smart warehouse transformation.

Application

Warehousing and Logistics

Challenges:
Traditional manual forklifts have low efficiency (handling approximately 200 pallets per day) , high error rate (About 5%), Difficult for nighttime operations due to fatigue and reduced visibility.
Complex warehouse environments: Narrow aisles (<1.5 meters) with dense shelving, Mixed cargo types with varying dimensions and stacking heights exceeding 6 meters, increasing the risk of misalignment or collapse

Technology Adaptation:
LiDAR SLAM Navigation: Enables autonomous localization and mapping without magnetic strips or QR codes. Dynamically adapt to shelf layout adjustments.
Vision-Based Pallet Recognition: Uses industrial cameras combined with AI algorithms to identify pallet shapes and stacking patterns. The system automatically adjusts fork width and lifting height for accurate and efficient handling.

Case:
Amazon Kiva Robots: By integrating autonomous forklifts into its logistics workflow, Amazon realizes automatic distribution from shelves to workstations. This integration boosted warehouse picking efficiency by 3 times , while reducing labor requirements by 50% , significantly improving operational automation and scalability.
Manufacturing Industry

Challenges:
Frequent delivery of production line components is required,such as in automotive plants where over 50 pallets need to be moved every hour. Manual handling is easy to fatigue-induced delays and errors, affecting production continuity and efficiency.

Technology Adaptation:
High-Load Hydraulic System: Designed load capacities of 5–10 tons , lifting heights of 4–6 meters , and positioning accuracy within ±3mm , ensuring precise and stable material supply.
Multi-Vehicle Coordination & Scheduling: Utilizes a Fleet Management System (FMS) to orchestrate the operations of 20+ autonomous forklifts simultaneously, dynamically optimizing routes and avoiding traffic congestion.

Case:
BMW Leipzig Plant: Autonomous forklifts are deployed to transport engines to the assembly line, payload 5 tons and positioning error less than 5mm . The on-time delivery rate has increased to 99.9% .
Tesla Gigafactory: Autonomous forklifts handle the fully automated transportation of battery modules from the storage area to the production line. This deployment has reduced labor costs by 60% and brought the accident rate down to zero.
Cold Chain and Hazardous Environments

Challenges:
In cold storage environment, manual transportation is inefficient (workers need to frequently go in and out to keep warm). The risk of handling hazardous materials is high (such as chemical raw material leakage).
Environmental Challenges: Extreme low temperatures (down to –30°C ), High humidity, flammable or explosive, Strong electromagnetic interference.

Technology Adaptation:
Low-Temperature Resistant Battery & Sealed Design: Equipped with lithium-ion battery packs that remain stable at –30°C , fully sealed motors and sensors to prevent condensation and ensure reliable operation in harsh conditions.
Intrinsic Safety Circuitry: Uses explosion-proof motors and flameproof enclosures that meet international standards such as ATEX and IECEx , making them suitable for use in chemical plants, oil depots, and other hazardous locations.

Case:
BASF Chemical Plant: Autonomous forklifts are deployed in explosion-proof zones to transport hazardous chemicals, payload 3 tons. Thanks to intrinsic safety design and advanced automation, the system has achieved zero accidents and improved delivery efficiency by 50% , significantly enhancing both operational safety and logistics performance in dangerous industrial settings.

Accessories

LiDAR

Scans the surrounding environment by emitting laser beams to generate high-precision 3D maps for use in SLAM (simultaneous localization and mapping) and obstacle detection.

Vision Camera (Industrial Camera)

Captures visual data such as floor textures, QR codes, shelf labels, and object shapes. Combined with deep learning algorithms to achieve advanced functions like path planning , object identification. Example: In e-commerce warehouse, the camera can recognize different pallet stack types and automatically adjust the forklift’s arm width for accurate and efficient loading and unloading.

Servo Motors and Drivers

Precisely control the forklift’s forward movement, steering, lifting, and tilting actions with fast response times (in milliseconds).