Multi-objective excavation trajectory optimization for unmanned electric shovels based on pseudospectral method

Zhang, Tianci; Fu, Tao; Song, Xueguan; Qu, Fuzheng

doi:10.1016/j.autcon.2022.104176

Cited by 14 publications

(8 citation statements)

References 37 publications

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“…From the above formula, the steering radius and centroid velocity of ES can be obtained as: Figure 5b shows the plane motion analysis of an ES crawler. The differential equation of motion of an ES center is shown in Equation (18).…”

Section: Trajectory Tracking Methods 41 Kinematics Model Of An Esmentioning

confidence: 99%

“…Figure 6a shows a Figure 5b shows the plane motion analysis of an ES crawler. The differential equation of motion of an ES center is shown in Equation (18).…”

Section: Trajectory Tracking Strategymentioning

confidence: 99%

“…The effectiveness of the proposed optimal mining trajectory is verified by a large number of simulations and experiments. Compared with other commonly used methods, the proposed framework is more competitive in terms of mining time and energy consumption [18]. An accurate dynamic model of tracked vehicles can improve the performance of control logic in critical driving scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Research on Path Planning and Trajectory Tracking of an Unmanned Electric Shovel Based on Improved APF and Preview Deviation Fuzzy Control

Fang

Wang

et al. 2022

Machines

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With the development and upgrading of intelligent mines, research on the unmanned walking of intelligent electric shovels (ES) has been carried out to improve the moving efficiency of extra-large excavators. This paper first introduces an electric shovel’s primary moving condition in an open-pit mine. According to the moving characteristics of the heavy-duty crawler, the artificial potential field (APF) algorithm is improved to plan the moving trajectory of the electric shovel and carry out simulation verification. A dynamic model of an electric shovel is established. A fuzzy control tracking method is proposed based on preview displacement and centroid displacement deviation. The robustness of the tracking algorithm is verified by multi-condition simulation. Finally, the electric shovel prototype is tested through path planning and tracking experiments. The experimental results show that the improved artificial potential field algorithm can plan an obstacle-free path that satisfies the movement of an electric shovel, and the electric shovel can quickly track the preset trajectory. The maximum deviation of the track tracking center of mass is no more than 10 cm, and the deviation of the heading angle when the shovel reaches the endpoint is within 2°.

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Section: Trajectory Tracking Methods 41 Kinematics Model Of An Esmentioning

confidence: 99%

“…Figure 6a shows a Figure 5b shows the plane motion analysis of an ES crawler. The differential equation of motion of an ES center is shown in Equation (18).…”

Section: Trajectory Tracking Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Path Planning and Trajectory Tracking of an Unmanned Electric Shovel Based on Improved APF and Preview Deviation Fuzzy Control

Fang

Wang

et al. 2022

Machines

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“…In [ 13 ], a solution strategy based on the GPM was presented to optimize the fuel-efficient winglet retractable climb trajectory for near-space variable-wing aircraft. In [ 14 ], a multi-objective excavation trajectory optimization framework based on the RPM is proposed for the trajectory planning of the unmanned electric shovel in autonomous mining scenarios. In [ 15 ], the trajectory optimization problem is numerically solved via a hp-pseudospectral sequential convex programming method, which iteratively solves a sequence of second-order cone programming subproblems until convergence is attained.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Planning of Autonomous Underwater Vehicles Based on Gauss Pseudospectral Method

Gan

Chu

2023

Sensors

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This paper aims to address the obstacle avoidance problem of autonomous underwater vehicles (AUVs) in complex environments by proposing a trajectory planning method based on the Gauss pseudospectral method (GPM). According to the kinematics and dynamics constraints, and the obstacle avoidance requirement in AUV navigation, a multi-constraint trajectory planning model is established. The model takes energy consumption and sailing time as optimization objectives. The optimal control problem is transformed into a nonlinear programming problem by the GPM. The trajectory satisfying the optimization objective can be obtained by solving the problem with a sequential quadratic programming (SQP) algorithm. For the optimization of calculation parameters, the cubic spline interpolation method is proposed to generate initial value. Finally, through comparison with the linear fitting method, the rapidity of the solution of the cubic spline interpolation method is verified. The simulation results show that the cubic spline interpolation method improves the operation performance by 49.35% compared with the linear fitting method, which verifies the effectiveness of the cubic spline interpolation method in solving the optimal control problem.

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“…Meng Y et al [ 10 ] established a force model of the bucket during the excavation process based on Coulomb theory, optimized the excavation trajectory using the optimal energy consumption, and verified it by EDEM simulation. Zhang T et al [ 11 ] proposed a multi-target trajectory planning framework for an MRS based on a pseudo-spectral method, which was used for autonomous excavation of the MRS and verified by simulation and experiment. Fan J et al [ 12 , 13 ] proposed a new electro-hydraulic hybrid MRS and optimized its hoist and crowd speeds with the goal of minimizing energy consumption per unit excavation mass.…”

Section: Introductionmentioning

confidence: 99%

Excavating Trajectory Planning of a Mining Rope Shovel Based on Material Surface Perception

Feng

Lin

et al. 2023

Sensors

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The mining rope shovel (MRS) is one of the core pieces of equipment for open-pit mining, and is currently moving towards intelligent and unmanned transformation, replacing traditional manual operations with intelligent mining. Aiming at the demand for online planning of an intelligent shovel excavation trajectory, an MRS excavating trajectory planning method based on material surface perception is proposed here. First, point cloud data of the material stacking surface are obtained through laser radar to perceive the excavation environment and these point cloud data are horizontally calibrated and filtered to reconstruct the surface morphology of the material surface to provide a material surface model for calculation of the mining volume in the subsequent trajectory planning. Second, kinematics and dynamics analysis of the MRS excavation device are carried out using the Product of Exponentials (PoE) and Lagrange equation, providing a theoretical basis for calculating the excavation energy consumption in trajectory planning. Then, the trajectory model of the bucket tooth tip is established by the method of sixth-order polynomial interpolation. The unit mass excavation energy consumption and unit mass excavation time are taken as the objective function, and the motor performance and the geometric size of the MRS are taken as constraints. The grey wolf optimizer is used for iterative optimization to realize efficient and energy-saving excavation trajectory planning of the MRS. Finally, trajectory planning is carried out for material surfaces with four different shapes (typical, convex, concave, and convex–concave). The results of experimental validation show that the actual hoist and crowd forces are essentially consistent with the planned hoist and crowd forces in terms of the peak value and trend variations, verifying the accuracy of the calculation model and confirming that the full bucket rate and various parameters meet the constraints. Therefore, the trajectory planning method based on material surface perception are feasible for application to different excavation conditions.

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Multi-objective excavation trajectory optimization for unmanned electric shovels based on pseudospectral method

Cited by 14 publications

References 37 publications

Research on Path Planning and Trajectory Tracking of an Unmanned Electric Shovel Based on Improved APF and Preview Deviation Fuzzy Control

Research on Path Planning and Trajectory Tracking of an Unmanned Electric Shovel Based on Improved APF and Preview Deviation Fuzzy Control

Trajectory Planning of Autonomous Underwater Vehicles Based on Gauss Pseudospectral Method

Excavating Trajectory Planning of a Mining Rope Shovel Based on Material Surface Perception

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