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An Improved Autonomous Emergency Braking Algorithm for AGVs: Enhancing Operational Smoothness Through Multi-Stage

Wenbo Li¹, Junting Qiu²

¹School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.

Sensors (Basel, Switzerland)

|April 12, 2025

Summary

This study introduces an improved Autonomous Emergency Braking (AEB) algorithm for automated guided vehicles (AGVs). The new AEB system enhances operational smoothness and safety by reducing sudden stops during industrial transport.

Keywords:

AEB algorithm AGV SLAM emergency stop avoidance industrial automation motion control obstacle avoidance algorithm path planning velocity smoothing

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Area of Science:

Robotics
Industrial Automation
Control Systems

Background:

Automated Guided Vehicles (AGVs) are crucial for industrial logistics.
Frequent starts/stops in AGVs cause mechanical wear, battery degradation, and navigation errors.
Existing emergency braking systems lack efficiency and smoothness.

Purpose of the Study:

To develop an improved Autonomous Emergency Braking (AEB) algorithm for AGVs.
To enhance AGV operational smoothness, safety, and efficiency.
To address limitations of conventional emergency stop strategies.

Main Methods:

Implemented a stepwise deceleration strategy for smoother braking.
Optimized AEB for both straight-line and turning scenarios, adjusting detection range.
Incorporated a velocity smoothing algorithm to prevent abrupt speed changes.

Main Results:

The improved AEB algorithm significantly reduced the frequency of sudden stops.
Demonstrated enhanced operational smoothness and safety in AGV applications.
Validated through real-world equipment testing and comparison with conventional methods.

Conclusions:

The proposed AEB algorithm effectively mitigates issues associated with frequent AGV stops.
The system offers improved performance, adaptability, and robustness in industrial environments.
This advancement contributes to more efficient and reliable AGV operations.