Navigation System for LHD Machines

Mäkelä, Hannu; Lehtinen, Hannu; Rintanen, K.; Koskinen, Kari

doi:10.1016/b978-0-08-042366-1.50052-x

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…The test system is shown in Figure 11. The LMS SCADAS ( 1 , SCM05) was used to record the data during the field test, and the sample frequency was set to 100 Hz according to [15]. Two IMUs ( 2 , 3 , Beijingsanchi, SC-AHRS-200A) were installed in the front frame and the rear frame, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…According to [15,25], the sampling frequency of the simulation was set to 100 Hz. The speed of the LHD vehicle was set to 14 km/h under normal running conditions and 9.5 km/h during the constant radius steering process.…”

Section: Simulation Setupmentioning

confidence: 99%

“…Infrastructure-based methods were applied during an early stage, but have not been widely used due to their cost and obstructions in the environment [8,15].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Model-Based Method for Estimating the Attitude of Underground Articulated Vehicles

Gao

Jin

2019

Sensors

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This paper presents a novel model-based method for estimating the attitude of underground articulated vehicles (UAV). We selected the Load–Haul–Dump (LHD) vehicle as our application object, as it is a typical UAV. First, we established the involved models of the LHD vehicle, including a kinematic model, the linear and angular constraints of a center articulation model, and a dynamic four degrees-of-freedom (DOF) yaw model. Second, we designed a Kalman filter (KF) to integrate the kinematic and constraint models with the data from an inertial measurement unit (IMU), overcoming gyroscope drift and disturbances in external acceleration. In addition, we designed another KF to estimate the yaw based on the dynamic yaw model. The accuracy of the estimations was further enhanced by data fusion. Then, the proposed method was validated by a simulation and a field test under different dynamic conditions. The errors in the estimation of roll, pitch, and yaw were 3.8%, 2.4%, and 4.2%, respectively, in the field test. The estimated longitudinal acceleration was used to obtain the velocity of the LHD vehicle; the error was found to be 1.2%. A comparison of these results to those of other methods showed that the proposed method has high precision. The proposed model-based method will greatly benefit the location, navigation, and control of UAVs without any artificial infrastructure in a global positioning system (GPS)-free environment.

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Section: Methodsmentioning

confidence: 99%

Section: Simulation Setupmentioning

confidence: 99%