Omnidirectional Forklift Obstacle Avoidance Control
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Solution Overview
Problem
Omnidirectional automatic forklifts face challenges in formulating effective obstacle-avoiding strategies and stop logic when encountering obstacles in logistics warehouses, requiring a method to safely navigate and manage obstacles while performing tasks.
Innovation Solution
A movement control method for omnidirectional automatic forklifts that involves detecting obstacles, calculating obstacle-avoiding deceleration based on distance, and adjusting speed to avoid obstacles, utilizing lidars and 3D cameras to determine effective obstacles and zones, and integrating sensor data with obstacle-avoiding logic to ensure safe navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the omnidirectional automatic forklift travels at a preset speed to maintain productivity, then the forklift can efficiently perform tasks, but it may collide with obstacles in the warehouse
Solution Approach 1:
The system performs preliminary obstacle detection using lidars and 3D cameras before the forklift reaches the obstacle. The controller calculates the distance to the obstacle and determines the appropriate deceleration in advance, allowing the forklift to maintain normal speed for most of the journey while ensuring safe stopping distance is available.
Solution Approach 2:
The system continuously monitors the environment using sensors (lidars, 3D cameras) and provides feedback to the controller. When an obstacle is detected, the controller adjusts the speed based on the distance feedback, creating a closed-loop control system that balances productivity and safety dynamically.
2Reliability
If the forklift performs emergency stop when obstacle distance is short, then collision is avoided, but the frequent emergency stops reduce productivity
Solution Approach 1:
The system changes the deceleration parameter dynamically based on the distance to the obstacle. When the distance is large, a smaller deceleration is applied; when the distance is short, emergency deceleration is applied. This parameter adjustment optimizes both safety and productivity by avoiding unnecessary emergency stops.
3Measurement precision
If the forklift uses multiple sensors (lidars and 3D cameras) to detect obstacles accurately, then obstacle detection precision is improved, but the device complexity increases
Solution Approach 1:
The system merges the functions of multiple sensors (lidars for distance measurement and 3D cameras for visual recognition) into a unified obstacle detection system. The controller integrates data from all sensors to comprehensively determine obstacle presence and distance, achieving high detection precision while managing system complexity through coordinated sensor operation.
Data Source
Figure 1~2A
Figure 2B~3B
Figure 4~5A
AI summary
The prevent invention relates to a movement control method for an omnidirectional automatic forklift (100), wherein the omnidirectional automatic forklift (100) comprises a vehicle body (110) and fork arms (120), the movement control method comprising: S101: controlling the omnidirectional automatic forklift (100) to travel at a first preset speed; S102: judging, when an obstacle is detected, the obstacle and determining an effective obstacle; S103: calculating a distance between the effective obstacle and the omnidirectional automatic forklift (100), and determining an obstacle-avoiding deceleration according to the distance; S104: controlling the omnidirectional automatic forklift (100) to travel at the obstacle-avoiding deceleration; and S105: judging whether the obstacle disappears, and returning to step S101 if the obstacle disappears. With the examples of the present invention, the omnidirectional safe obstacle avoidance is realized in an omnidirectional automatic forklift (100).