An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

Fu, Zhuang; Feng, Xin; Duan, Xiaoming; Fu, Zeyu

doi:10.1177/0954407019900031

Cited by 10 publications

(4 citation statements)

References 26 publications

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“…Terminal automated guided vehicle in automated container terminal Terminal AGV was first used in the European Combined Terminal in the port of Rotterdam, which plays a role in replacing manually driven trucks that transport containers between the ship and yard handling areas according to the preset path determined by a set of rules (Li et al, 2021;Sun et al, 2023). The main tasks to control the AGV system in the transportation operation of the ACT can be listed as task dispatching, path planning and navigation (Fu et al, 2020;Yue and Fan, 2022). Studies related to terminal AGV systems mainly focus on task dispatching and path planning problems.…”

Section: Literature Reviewmentioning

confidence: 99%

AGV robot for laser-SLAM based method testing in automated container terminal

Yang,

Cao,

Liu

et al. 2023

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Purpose Magnet spot is the primary method to develop the automated guided vehicle (AGV) guidance system for many automated container terminals (ACT). Aiming to improve the high flexibility of AGV operation in ACT, this paper aims to address the problem of technical stability leading to ACT production paralysis and propose a mini-terminal AGV robot for testing laser simultaneous location and mapping (SLAM)-based methods in ACT operation scenarios. Design/methodology/approach This study developed a physical simulation robot for terminal AGV operations, providing a platform to test technical solutions for applying laser navigation-related technologies in ACTs. Then, the terminal-AGV navigation system framework is designed to apply the laser-SLAM-based method in the physical simulation robot. Finally, the experiment is conducted in the terminal operation scenario to verify the feasibility of the proposed framework for lased-SLAM-based method testing and analyze the performance of the different mini-terminal AGV robots. Findings A series of experiments are conducted to analyze the performance of the proposed mini-terminal AGV robot for laser-SLAM-based method testing. The experimental results show the validity and effectiveness of the AGV robot and AGV navigation system framework with better local map matching, loopback and absolute positional error. Originality/value The proposed mini-terminal AGV robot and AGV navigation system framework can provide a platform for innovative laser-SLAM-based method testing in ACTs applications. Therefore, this study can effectively meet the high requirements of ACT for maturity and stability of the laser navigation technical.

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Section: Literature Reviewmentioning

confidence: 99%

AGV robot for laser-SLAM based method testing in automated container terminal

Yang,

Cao,

Liu

et al. 2023

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“…where, A 0 is the system matrix and the non-zero elements are shown in (4), where, v ie is the earth rotation rate, R M and R N are the short and major axis of the Earth, C n b is the b-frame to n-frame transformation matrix. F 0 is the noise distribution matrix, j 0 is the system noise vector, W b g and W b a are the random walk noise of gyroscope and accelerometer respectively.…”

Section: Gnss/ins Integration Algorithmmentioning

confidence: 99%

“…Localization system is of great significance for autonomous vehicle in path planning, path tracking and motion control. [1][2][3] There are many sensors that can be used in autonomous vehicle for localization, such as GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System), 4 vehicle odometer and steering wheel angle, [5][6][7] vision sensors, 8 laser radar, 9 wireless signals, 10 and so on. Of all these sensors, the fusion of GNSS/INS and vehicle chassis information is one of the most popular approaches for localizing the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Vehicle heading angle and IMU heading mounting angle improvement leveraging GNSS course angle

Liu

Xia³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Using vehicle chassis information can significantly improve the accuracy of GNSS/INS fusion system when GNSS signals are unavailable. The IMU mounting angles play an important role when fusing vehicle chassis information with GNSS/INS system. However, the IMU mounting angles cannot be directly measured conveniently. This paper proposed a new method to simultaneously improve the estimation accuracy of both the vehicle heading angle and the IMU heading mounting angle by leveraging GNSS course angle as an additional measurement. Firstly, an error state Kalman filter is constructed with state variables including the attitude errors, velocity errors, position errors, gyro, and acceleration bias errors, IMU mounting angle and vehicle velocity scale factor. The GNSS course angle is augmented to the Kalman filter as a measurement when the vehicle travels in straight line. Then, the observability analysis of the GNSS/INS/Onboard sensors fusion system is carried out and the results show that the observability of the system using GNSS course angle is better than that of only using vehicle velocity and non-holonomic constraint (NHC) as measurements if the heading mounting angle and pitch mounting angle are not zero. Finally, the experiment results show that the accuracy of the vehicle heading angle and the IMU heading mounting angle can be improved by 14% judging from the lateral velocity error of vehicle compared to that of only using vehicle velocity and NHC as measurements.

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“…Self-propelled robots operate in open environments, necessitating path planning and trajectory monitoring. This challenge has sparked interest among many scientists and manufacturing companies [4], [5]. The trajectory and navigation setup for self-propelled robots involves using linear, intelligent, and hybrid control methods.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking control based on genetic algorithm and proportional integral derivative controller for two-wheel mobile robot

Ha,

Thi Thuong,

Ngoc Truc

2024

Bulletin EEI

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This paper uses the genetic algorithm (GA) to optimize the proportional integral derivative (PID) controller parameters to present the motion control design for a two-wheeled mobile robot autonomous system. The GA algorithm determines a collision-free travel curve for a robot with a tangential velocity restriction constraint. A trajectory-tracking controller based on the PID control structure is developed to monitor the calculated route curves for the mobile robot. Simulation results show the effectiveness of the GA-PID controller compared to the PID controller. The GA-PID controller demonstrates improved performance in trajectory tracking and collision avoidance, making it suitable for controlling the motion of two-wheeled mobile robots. The GA's optimization process allows for better tuning of the PID controller parameters, resulting in more efficient and accurate robot motion control. The results suggest that the proposed GA-PID controller is a promising approach for enhancing mobile robots' autonomous navigation capabilities.

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An improved integrated navigation method based on RINS, GNSS and kinematics for port heavy-duty AGV

Cited by 10 publications

References 26 publications

AGV robot for laser-SLAM based method testing in automated container terminal

AGV robot for laser-SLAM based method testing in automated container terminal

Vehicle heading angle and IMU heading mounting angle improvement leveraging GNSS course angle

Trajectory tracking control based on genetic algorithm and proportional integral derivative controller for two-wheel mobile robot

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