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

The automated guided vehicle (AGV) is widely used in industrial environments for goods transportation. However, issues such as mechanical wear, reduced battery life, navigation error accumulation, and decreased operational efficiency caused by frequent starts and stops need to be addressed. This pap...

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Vydáno v:Sensors (Basel, Switzerland) Ročník 25; číslo 7; s. 2041
Hlavní autoři: Li, Wenbo, Qiu, Junting
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 25.03.2025
MDPI
Témata:
AEB algorithm
AGV
Algorithms
Automatic guided vehicles
Automation
Batteries
Design
industrial automation
Kinematics
Localization
obstacle avoidance algorithm
path planning
Vehicles
Velocity
velocity smoothing
Wheels
AGV
obstacle avoidance algorithm
SLAM
motion control
AEB algorithm
velocity smoothing
emergency stop avoidance
industrial automation
path planning
ISSN:1424-8220, 1424-8220
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Shrnutí:The automated guided vehicle (AGV) is widely used in industrial environments for goods transportation. However, issues such as mechanical wear, reduced battery life, navigation error accumulation, and decreased operational efficiency caused by frequent starts and stops need to be addressed. This paper proposes an improved Autonomous Emergency Braking (AEB) algorithm to tackle these problems. The algorithm employs a stepwise deceleration strategy, effectively reducing the frequency of sudden stops and enhancing the system’s operational smoothness. The AEB algorithm not only considers straight-line driving scenarios but also optimizes deceleration strategies for turning scenarios, adjusting the deceleration detection range according to the turning trajectory. Additionally, a velocity smoothing algorithm is designed to ensure that speed changes during deceleration are gradual, avoiding abrupt speed variations that could impact the system. The feasibility of the AEB algorithm is validated through testing on actual equipment, and its performance is compared to that of a conventional emergency stop strategy. Experimental results show that the AEB algorithm significantly reduces the number of sudden stops, improves the AGV’s operational smoothness and safety, and demonstrates excellent adaptability and robustness across different operational conditions.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s25072041