How can electric pallet trucks achieve safe passage in high-density shelf areas through LiDAR?

Technical background: Safety challenges in high-density shelf areas
As the area with the highest utilization rate of storage space, the high-density shelf area usually has a channel width of only 1.5-2.5 meters, the shelf spacing is less than 1 meter, and the height of the cargo stacking can reach more than 10 meters. This environment poses three core challenges to handling equipment:
Spatial constraints: Traditional pallet trucks are prone to scratches or collisions when passing through the gaps between shelves due to their lack of environmental perception.
Dynamic interference: Factors such as the slight displacement of shelf stacking and the vibration of forklift operations may change the real-time passage conditions of the channel.
Balance between efficiency and safety: While pursuing high throughput, it is necessary to avoid the risk of cargo overturning due to sudden acceleration or sudden braking.
The introduction of LiDAR technology provides a possibility for solving the above problems. By building a three-dimensional environmental model, electric pallet trucks can achieve obstacle recognition and path planning with millimeter-level accuracy, fundamentally improving the safety of operations in high-density shelf areas.

Technical analysis: How LiDAR enables dynamic acceleration control
1. Environmental perception: building a three-dimensional safety barrier
LiDAR generates real-time three-dimensional point cloud data of the shelf area by emitting laser beams and measuring the time difference of reflected light. The data contains the following key information:
Shelf position: accurately identify the position and inclination angle of shelf columns and beams with an error of less than 5 mm.
Aisle width: dynamically calculate the real-time distance between the vehicle and the shelves on both sides with an error of less than 1 cm.
Obstacle identification: distinguish between static obstacles (such as shelves) and dynamic obstacles (such as pedestrians and forklifts), and predict their movement trajectories.

2. Dynamic acceleration curve: evolution from linear to adaptive
The acceleration curve of traditional pallet trucks is usually a fixed slope, which is difficult to adapt to complex environments. The addition of LiDAR enables acceleration control to enter the adaptive stage:
Initial stage: The vehicle starts at a constant speed of 2km/h, and the LiDAR continuously scans the shelf gap within 5 meters in front.
Mid-stage adjustment: When the channel width changes, the system dynamically adjusts the acceleration slope according to the remaining distance and gap width. For example, if the channel narrows to 1.8 meters at 10 meters ahead, the system will reduce acceleration 2 seconds in advance to ensure that the vehicle passes at a safe speed.
End fine-tuning: When the gap between the shelves is 1 meter, the system enters the fine control mode and controls the speed fluctuation within ±0.1km/h through the PID algorithm.

3. Multimodal collaboration: Improving adaptability to complex scenarios
LiDAR does not work in isolation, but forms collaboration with other sensors of the vehicle:
Inertial navigation system (INS): Provides vehicle posture and motion state data to assist LiDAR in correcting point cloud distortion.
Visual sensor: Identify labels on shelves (such as barcodes and QR codes) to verify the accuracy of LiDAR data.
Ultrasonic sensor: Provides supplementary detection in LiDAR blind spots (such as the bottom of the shelf).

Scenario application: Verification from theory to practice
1. Typical scenario 1: Narrow channel obstacle avoidance
In a channel with a width of only 2 meters, LiDAR can detect a slight tilt of the shelf column 15 meters in advance (such as due to uneven stacking of goods). The system achieves safe passage through the following steps:
Warning stage: When the column tilt angle exceeds 2°, the deceleration program is triggered to reduce the acceleration by 50%.
Path planning: According to the tilt direction and vehicle width, the driving trajectory is dynamically adjusted to ensure that the tires and the shelves maintain a safe distance of 20 cm.
Feedback correction: If the vehicle deviates from the planned path due to inertia, the laser radar adjusts the steering angle in real time to avoid contact with the shelf.

2. Typical scenario 2: dynamic obstacle avoidance
When the forklift drives out from behind the shelf, the laser radar can identify its movement trajectory 8 seconds in advance. The system adopts the following strategies:
Predictive deceleration: According to the forklift speed and the current position of the vehicle, the safe distance is calculated and the deceleration program is started 3 seconds in advance.
Cooperative avoidance: If the forklift and the vehicle have an intersecting path, the system cooperates with the forklift through the vehicle communication module (such as Wi-Fi 6) to give priority to the forklift to complete the avoidance.
Emergency braking: When the obstacle distance is less than 0.5 meters, the electromagnetic brake system is triggered to completely stop the vehicle within 0.3 seconds.

3. Typical scenario 3: Shelf displacement monitoring
Lidar can monitor the slight displacement of shelf columns in real time (such as caused by ground subsidence). When the displacement exceeds 5 mm, the system takes the following measures:
Risk assessment: Combine shelf structure parameters and cargo weight to calculate the impact of displacement on channel traffic.
Path reconstruction: If the displacement causes the channel width to decrease, the system automatically adjusts the acceleration curve to reduce the speed fluctuation when the vehicle passes.
Early warning notification: The displacement alarm is sent synchronously through the on-board display and the warehouse management system (WMS) to prompt managers to check the stability of the shelf.

Industry value: Comprehensive improvement from safety to efficiency
1. Safety benefits
Reduced accident rate: After an e-commerce warehouse applied this technology, the collision accidents between pallet trucks and shelves decreased by 90%, and the cargo damage rate dropped to less than 0.1%.
Personnel protection: Through the dynamic obstacle avoidance function, the conflict incidents between personnel and vehicles were reduced by 85%, significantly improving the safety of warehousing operations.
2. Efficiency improvement
Improved channel utilization: Adaptive acceleration control increases the average speed of vehicles in complex channels by 30%, while maintaining a zero collision record.
Optimized loading and unloading efficiency: Reduce downtime caused by accidents, and increase the average daily throughput of a single pallet truck by 20%.
3. Enhanced compliance
The application of LiDAR technology enables electric pallet trucks to meet the ISO 3691-5 standard for industrial vehicle safety performance, helping companies pass international certification and expand global markets.