CN115544768A - A method and system for generating an autonomous excavation operation trajectory - Google Patents

Abstract

The invention provides a method and system for generating an autonomous excavation operation trajectory, which relate to the technical field of excavators, including: analyzing the excavation operation movement by integrating the operation characteristics of skilled operators on the excavator experiment platform, and obtaining an excavation path model; The path model uses a segmented Bezier curve to represent the excavation trajectory; based on the segmented Bezier curve, the time of the excavation operation movement is used as the optimization target, and the continuity constraint, the boundary constraint, and the dynamic feasibility constraint are used as the constraint conditions, Establish the objective function of the time-optimal trajectory generation problem; based on the discretization method, reconstruct the time-optimal trajectory generation problem into a solvable second-order cone optimization problem, and iteratively solve the second-order cone optimization problem to obtain the time-optimal mining track. The invention enables the machine to complete the operation task in the shortest time, and improves the operation efficiency of the excavator.

Description

A method and system for generating an autonomous excavation operation trajectory

technical field

The invention relates to the technical field of excavators, in particular to a method and system for generating an autonomous excavation trajectory.

Background technique

Excavators are widely used and play an important role in urban and rural construction, transportation, emergency rescue and disaster relief. In recent years, with the development of computer and control technology, the development of autonomous excavators has attracted the attention of the construction machinery industry. So far, the operation of excavators relies heavily on the operation of skilled operators, which leads to low efficiency of excavation operations. In addition, in the face of harsh and changeable operating environments, the safety of operators is greatly threatened. In view of the above two aspects The reason is that there is an urgent need to develop autonomous excavators to realize autonomous excavation operations. The key technology is to independently generate efficient motion trajectories. The efficiency of excavation operations means that the excavation process requires optimal time allocation.

Aiming at the problem of generating the optimal excavation trajectory of the excavator, the prior art discloses a method of performing dynamic modeling on the excavator to generate the excavation trajectory with the minimum torque, and using piecewise polynomials to generate a minimum A method for torque mining trajectories. Although the above method obtains the optimal mining trajectory, the problem of optimal time allocation is still unsolved. The optimal mining trajectory optimization for time generally includes heuristic and optimization methods. The prior art proposes a heuristic algorithm to allocate the most However, for large-scale mining trajectory generation, this method is computationally expensive and difficult to meet real-time trajectory generation.

Time optimality means that the driver can increase the speed and acceleration appropriately without violating the physical limit of the machine, even reaching its physical limit state, so that the machine can complete the task in the shortest time, thereby improving efficiency. The optimality problem, the previous method is usually to satisfy the physical limit constraints of the machine, and convert it into a type of nonlinear optimization problem for solving. However, this kind of scheme does not fully exploit the performance of the driver, that is, it cannot guarantee the optimal time. In addition, the above schemes all need to provide an initial solution when solving the problem. The solution of the problem depends heavily on the selection of the initial solution, which may lead to falling into a local solution, and it is difficult to guarantee the global optimality.

Contents of the invention

In view of this, the present invention proposes a method and system for generating an autonomous excavation trajectory to solve the technical problem of how to ensure the optimality of excavation trajectory time in the prior art.

To achieve the above object, the present invention is achieved through the following technical solutions:

The invention provides a method for generating an autonomous excavation operation trajectory, comprising the following steps:

On the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement and obtain the excavation path model;

Based on the excavation path model, a segmented Bezier curve is used to represent an excavation trajectory;

Based on the segmented Bezier curve, the time of the excavation operation is used as the optimization target, and the continuity constraint, the boundary constraint, and the dynamic feasibility constraint are used as the constraint conditions to establish the objective function of the time optimal trajectory generation problem;

Based on the discretization method, the time-optimal trajectory generation problem is reconstructed into a solvable second-order cone optimization problem, and the second-order cone optimization problem is solved iteratively to obtain the time-optimal mining trajectory.

Preferably, the excavator experimental platform is equipped with an inclination sensor and an absolute encoder, and the inclination sensor and the absolute encoder are respectively used to measure the movement of the rotary joint, the boom, the arm, and the bucket joint during the movement of the excavator. The variation of the angle value is collected and processed by the computer, and the trajectory tracking is finally carried out by the controller.

Preferably, the operation characteristic of the skilled operator is obtained by analyzing the digging path topology information of the skilled operator based on the digging path generation rules of the skilled operator for the digging task.

Preferably, on the excavator experimental platform, the operation characteristics of the skilled operator are integrated to analyze the excavation operation movement, and the excavation path model is obtained, including:

On the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement, and the topological information of the trajectory in the joint space is obtained;

Processing the topological information of the trajectory in the joint space by means of timing signal alignment, so that the data lengths in the topological information of the trajectory in the joint space are consistent;

performing noise reduction processing on the topological information of the trajectory in the joint space by using a moving average filtering method;

Taking the average value of multiple groups of joint space trajectories in the topology information of the trajectories in the joint space to obtain an average mining path;

Transform the average mining path into the pose space, use the Douglas-Peucker algorithm to find key passing points, and establish the mining path model.

Preferably, the segmented Bezier curve satisfies the following constraints:

Path point constraints to ensure that the trajectory passes through key path points;

Boundary value constraints, set the velocity and acceleration values of the excavation operation trajectory at the start and end points of the trajectory to meet the state requirements of the excavation operation;

Continuity constraints ensure that the order derivatives of the two connected trajectories are continuous at the breakpoints, and a smooth trajectory is obtained.

The present invention also provides an autonomous excavation operation trajectory generation system, including:

The acquisition module is used to integrate the operation characteristics of skilled operators on the excavator experimental platform to analyze the excavation operation movement and obtain the excavation path model;

a representation module for representing mining trajectories by segmented Bezier curves;

Establishing a module, which is used to use the time of excavation operation movement as the optimization target, with continuity constraints, boundary constraints, and dynamic feasibility constraints as constraints, to establish the objective function of the time-optimal trajectory generation problem;

The processing module is used to reconstruct the time-optimal trajectory generation problem into a solvable second-order cone optimization problem, and iteratively solve the second-order cone optimization problem to obtain the time-optimal mining trajectory.

Compared with the prior art, the beneficial effect of the present invention is that: the present invention proposes a method and system for generating an autonomous excavation operation trajectory, including: analyzing the excavation operation movement on the excavator experimental platform by integrating the operation characteristics of skilled operators, and obtaining An excavation path model; based on the excavation path model, a segmented Bezier curve is used to represent the excavation trajectory; based on the segmented Bezier curve, the time of the excavation operation movement is used as an optimization target, and the continuity constraint, boundary constraint, Dynamic feasibility constraints are used as constraints to establish the objective function of the time-optimal trajectory generation problem; based on the discretization method, the time-optimal trajectory generation problem is reconstructed into a solvable second-order cone optimization problem, and the second-order cone optimization problem is The iterative solution is used to obtain the time-optimal excavation trajectory, so that the machine can complete the task in the shortest time and improve the operating efficiency of the excavator.

Description of drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiment. The drawings are only for the purpose of illustrating a preferred embodiment and are not to be considered as limiting the invention. Also throughout the drawings, the same reference numerals are used to designate the same parts. In the attached picture:

Fig. 1 is a flow chart of a method for generating an autonomous excavation operation trajectory provided by an embodiment of the present invention;

Fig. 2 is a schematic diagram of excavation track analysis and wayfinding points for skilled operators provided by the embodiment of the present invention;

Fig. 3 is a schematic diagram of the motion state of the rotary joint of the excavator provided by the embodiment of the present invention;

Fig. 4 is a schematic diagram of the joint motion state of the arm of the excavator provided by the embodiment of the present invention;

Fig. 5 is a schematic diagram of the kinematic state of the arm joint of the excavator provided by the embodiment of the present invention;

Fig. 6 is the joint motion state of the excavator bucket provided by the embodiment of the present invention;

Fig. 7 is a schematic diagram of trajectory comparison in the pose space of the excavator provided by the embodiment of the present invention;

FIG. 8 is a schematic structural diagram of an autonomous excavation trajectory generation system provided by an embodiment of the present invention.

detailed description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure, and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and examples.

The purpose of the present invention is to provide a method and system for autonomous excavation trajectory generation, which solves the technical problem of how to ensure the optimality of excavation trajectory time in the prior art.

Referring to Fig. 1, a method for generating an autonomous excavation operation trajectory includes the following steps:

Step S101: On the excavator experimental platform, integrate the operation characteristics of skilled operators to analyze the excavation operation movement, and obtain the excavation path model;

Step S102: Based on the excavation path model, the excavation trajectory is represented by a segmented Bezier curve;

Step S103: Based on the segmented Bezier curve, the time of excavation operation movement is used as the optimization target, and the continuity constraint, boundary constraint, and dynamic feasibility constraint are used as constraint conditions to establish an objective function for the problem of time-optimal trajectory generation, Specifically include:

In order to generate motion as fast as possible and satisfy the kinematic constraints of four axes, a function τ(t) is introduced to map the time domain variable t to the imaginary domain variable τ. The following formula is used to describe the mapping relationship between the imaginary domain and the time domain:

In the formula, T={T ₀ , T ₁ ,...T _N ] is the time series of each trajectory of the route.

(1) Objective function

In order to improve the efficiency of autonomous excavator operation, it is necessary to reduce the total time of excavation operation under the dynamic constraints of the machine, so the invention takes the time of excavation operation movement as the optimization target. When the total time required to perform the mining task is T _S , the optimization objective can be written as follows:

For the solution of this nonlinear optimization problem, it needs to be converted into a convex optimization form, so that the global optimal solution can be obtained without depending on the initial value. Based on this, two functions a(τ), (τ) are introduced.

Simultaneous order:

b _i (τ)≥0

After the above conversion, the velocity and acceleration continuity constraints, boundary constraints and kinematics feasibility constraints of segmented trajectories can be expressed by a(τ), b(τ).

(2) Continuity constraints:

B′ _i (1)a _i (1)+B″ _i (1)b _i (1)=B′ _i+1 (0)a _i+1 (0)+B″ _i+1 (0)b _{i +1} (0)

(3) Boundary constraints:

B′ ₀ (0)a ₀ (0)+B″ ₀ (0)b ₀ (0)=a ₀

B′ _N (1)a _N (1)+B″ _N (1)b _N (1)=a _f

(4) Dynamic feasibility constraints:

-a _max ≤B′ _i (s)a _i (s)+B″ _i (s)b _i (s)≤a _max

In the formula, v ₀ , v _f and a ₀ , a _f are the velocity and acceleration at the beginning and end of the trajectory, respectively; v _max , a _max are the maximum velocity and maximum acceleration of the digging movement, respectively.

Step S104: Based on the discretization method, reconstruct the time-optimal trajectory generation problem into a solvable second-order cone optimization problem, and iteratively solve the second-order cone optimization problem to obtain the time-optimal mining trajectory.

a_i(τ)设定为分段恒定，则b_i(τ)写 成：In order to obtain the global optimal solution of the above optimization problem, the above trajectory generation problem needs to be reconstructed into a standard second-order cone optimization form. In the present invention, each track τ∈[0,1] is divided into M parts, so a _i (τ), b _i (τ) are also discretized into

a _i (τ) is set to be piecewise constant, then b _i (τ) is written as:

和

则目标函数可以改写成：Therefore, the introduction of slack variables

and

Then the objective function can be rewritten as:

In the formula, m=0, 1,..., M-1, i=0, 1,...N. At the same time, there is the following formula:

Among them, the above two inequalities can be recorded as the following second-order cone form:

In the formula, m=0, 1,..., M-1, i=0, 1,...N.

Wherein, m=0, 1, . . . , M, i=0, 1, . . . N.

The velocity and acceleration continuity constraints of the previous segmented trajectories, the boundary value constraints of the mining trajectories, and the kinematic feasibility constraints of the trajectories can also be written in a discrete form. Finally, the objective function and constraints of the original trajectory generation problem can be reconstructed into a second-order cone optimization problem:

min A ^T d

组成的向 量，

此轨迹生成问题是一个标准的二阶锥优化问题，对于此类 凸优化问题可以实时迭代优化求解，获取全局最优挖掘轨迹。In the formula, the continuity constraint and the boundary value constraint are uniformly recorded as the equality constraint (A _eq x=b _sq ), the dynamic feasibility constraint is recorded as the inequality constraint (A _is x≤b _is ), and the optimization variable x is given by

composed of vectors,

This trajectory generation problem is a standard second-order cone optimization problem. For this kind of convex optimization problem, real-time iterative optimization can be solved to obtain the global optimal mining trajectory.

The invention provides a method for generating an autonomous excavation operation trajectory, which can obtain the optimal excavation trajectory in time, enable the machine to complete the operation task in the shortest time, and improve the operation efficiency of the excavator.

Further, realizing the autonomous operation of the excavator must rely on sensing technology, which is the basis for realizing autonomous operation. For this reason, the present invention configures an inclination sensor and an absolute encoder on the excavator experimental platform, and the inclination sensor and the absolute encoder are respectively used to measure the variation of the angle value of the rotary joint, the boom, the arm, and the bucket joint during the movement of the excavator, and the data is collected and processed by the computer, and the trajectory is tracked by the controller .

Further, the job characteristics of the skilled operator are obtained by analyzing the topological information of the skilled operator's digging path based on the digging path generation rules of the skilled operator for the digging task.

For a given excavation task, the excavation motion requires the planning of bucket tip motion in pose space, whereas excavator trajectory generation is usually done in joint space. Therefore, it is necessary to convert the angle value in the joint space to the pose space to complete the mutual conversion between the joint space and the pose space. The DH parameters are shown in Table 1. is (θ ₁ , θ ₂ , θ ₃ , θ ₄ ), then the pose space coordinates O ₄ (x, y, z, ξ) of the bucket tooth tip can be obtained by the following formula:

In the formula, a ₁ , a ₂ , a ₃ , and a ₄ represent the connecting rod lengths of the slewing, boom, arm and bucket joint axes respectively, and d ₁ represents the connecting rod offset between the X ₀ and X ₁ axes.

Table 1 D-H parameters of SWE50E mining robot

Before analyzing the topology information of the excavation path of the skilled operator, in order to establish the excavation path generation rules of the skilled operator for the trenching task (trapezoidal trench), the complete operation process can be divided into five stages for the trench digging : Inserting the tip of the bucket, dragging the bucket, lifting the bucket, turning to the unloading point, turning to the digging point.

The analysis of the excavation rules comes from the excavation trajectory formed by the skilled driver (more than 10 years of excavation experience) who has dug the trench many times. First, in the preparation for excavation stage, the starting position of the bucket is selected as the position where the bucket can easily move to the starting point of excavation , the initial attitude of the bucket is that the angle between the bucket and the ground is the direction with less resistance to cutting soil (usually the angle between the bucket and the ground is 30°-60°). Second, during the bucket dragging stage, keep the bucket It can be filled with excavated materials and quickly complete the horizontal dragging. The third is the bucket lifting stage. After completing step two, the bucket is lifted and rotated to keep the excavated materials from falling out of the bucket. In the soil stage, complete the lifting of the bucket, keep the excavation action unchanged, and quickly rotate to the unloading point (the invention is set to rotate counterclockwise 90°), decelerate when the bucket is close to the unloading point and complete the unloading, and finally, rotate to the initial excavation During the point stage, the working device maintains the state of the previous stage, and adjusts to the pose of the first stage when approaching the excavation point.

Further, on the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement, and the excavation path model is obtained, including:

On the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement, and the topological information of the trajectory in the joint space is obtained;

Processing the topological information of the trajectory in the joint space by means of timing signal alignment, so that the data lengths in the topological information of the trajectory in the joint space are consistent;

performing noise reduction processing on the topological information of the trajectory in the joint space by using a moving average filtering method;

Taking the average value of multiple groups of joint space trajectories in the topology information of the trajectories in the joint space to obtain an average mining path;

Transform the average mining path into the pose space, use the Douglas-Peucker algorithm to find key passing points, and establish the mining path model.

After the trajectory of the skilled operator is generated through the above process, we need to analyze the topological information of the trajectory in the joint space, as shown in Figure 2. First, the data is processed by aligning the timing signals to make the data lengths consistent. , it is necessary to specify excavation tasks to carry out multiple sets of tests, and the operator cannot guarantee that the initial state of each test process is completely consistent. Then, the use of moving average filtering can reduce the interference of noise signals on the generation of excavator trajectories. There will be a certain degree of impact on the hydraulic cylinder, which will generate corresponding noise interference. Finally, the statistical average excavation path is obtained by taking the average value of multiple sets of trajectories for the excavation path of the skilled operator.

Since the mining task requires path planning in the pose space, we need to transform the joint space trajectory obtained above into the pose space for processing. In addition, in view of the fact that the excavation path obtained by the skilled operator is extremely poor, its geometry and time distributions are far from optimal, therefore, they are useless or even detrimental for trajectory optimization, however, topological information of manually mined paths is essential as it reflects human intentions (i.e. the fastest mining and stable operation), in order to preserve the topological information of the found path and improve the efficiency and quality of trajectory generation, the present invention proposes an intelligent path point selection strategy to generate sparse mining paths, and the key path points obtained in this way provide a basis for trajectory optimization With a large degree of freedom, the selection strategy of the waypoints in the present invention borrows an idea from the Douglas-Peucker algorithm. Once all the waypoints are found, we can generate a trajectory that satisfies the optimal trajectory of the dynamic constraints.

Further, the trajectory of the excavation operation needs to pass through the critical path point p, so these critical path points need to be connected by a series of curves. The present invention uses a Bezier curve to represent the excavation trajectory, and the n-order Bezier curve can ensure that the n-1 order trajectory It is continuous and has a good convex hull, which is beneficial to the subsequent optimization solution, but the order of the curve is proportional to the number of control points.

The n-order piecewise Bezier curve parameterized by τ is expressed as follows:

表示第i段贝塞尔曲线上的第j个控制点，

表示组合数，虚参数 τ∈[0，1],为保证生成的时间最优轨迹的光滑性，本发明选取分段贝塞尔曲线的 阶数n为5,并且分段贝塞尔曲线须满足如下约束：In the formula,

Indicates the jth control point on the i-th Bezier curve,

Represents the number of combinations, the virtual parameter τ∈[0,1], in order to ensure the smoothness of the generated time optimal trajectory, the present invention selects the order n of the segmented Bezier curve as 5, and the segmented Bezier curve must Satisfy the following constraints:

(1) Path point constraints: ensure that the trajectory passes through key path points.

(2) Boundary value constraint: set the velocity and acceleration values of the excavation operation trajectory at the start and end points of the trajectory to meet the state requirements of the excavation operation.

(3) Continuity constraints: ensure that the n-1 order derivatives of the two connected trajectories are continuous at the breakpoint, and a smooth trajectory is obtained.

As shown in Figure 8, the present invention also provides a system 12 for autonomous excavation operation trajectory generation, including:

Obtaining module 1201, used to integrate the operation characteristics of skilled operators on the excavator experimental platform to analyze the excavation operation movement, and obtain the excavation path model;

A representation module 1202, configured to represent the excavation trajectory through a segmented Bezier curve;

Build module 1203, be used for taking the time of excavation operation movement as optimization target, with continuity constraint, boundary constraint, dynamic feasibility constraint as constraint condition, establish the objective function of time optimal trajectory generation problem;

The processing module 1204 is used to reconstruct the time-optimal trajectory generation problem into a solvable second-order cone optimization problem, and iteratively solve the second-order cone optimization problem to obtain the time-optimal mining trajectory.

The invention provides an autonomous excavation operation trajectory generation system, which can obtain the optimal excavation trajectory in time, enable the machine to complete the operation task in the shortest time, and improve the operation efficiency of the excavator.

In order to verify the feasibility of the scheme, this paper compares the simulation results with the measured data. The measured data include the angle values of each joint in the process of digging, turning, dumping, and returning when the excavator is performing operations. Repeating 7 cycles counts as one excavation cycle. When the engine speed of the excavator is 1500rpm, in order to ensure the validity of the measured data, a total of 15 excavations were carried out for analysis and comparison, which is convenient for comparative analysis. This article only analyzes one excavation cycle. The kinematic feasibility constraints of each joint are shown in Table 2.

Table 2 Dynamic feasibility constraints of working devices

Figures 3 to 6 show the angle, velocity, and acceleration curves of each joint during excavation. It can be seen that the time required for the method proposed in this paper (red dotted line) is 10.7s less than the measured time for completing a excavation cycle. The time (blue solid line) is 11.0s, which shows that the method in this paper can make full use of the physical limit of the actuator to generate the minimum time mining trajectory.

In order to verify the feasibility of the scheme, analyze the characteristics of the trajectories of the two in the pose space, as shown in Figure 7, it can be seen that the trajectories of the two are generally similar, and the optimized trajectory (dotted line) has a large local change, which may be Because when the excavation task is performed under this power, the performance of the excavator is fully exerted, and at the same time, the speed and acceleration reach the limit state at this moment, which causes a large impact on the excavator, resulting in a local mutation of the trajectory.

Obviously, those skilled in the art can carry out various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Like this, if these modifications and variations of the present invention belong to the scope of the claims of the present invention and equivalent technologies thereof, It is intended that the present invention also encompasses such changes and modifications.

Claims (6)

1. A method for autonomous excavation operation track generation, is characterized in that, comprises the following steps: On the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement and obtain the excavation path model; Based on the excavation path model, a segmented Bezier curve is used to represent an excavation trajectory; Based on the segmented Bezier curve, the time of the excavation operation movement is used as the optimization target, and the continuity constraint, the boundary constraint, and the dynamic feasibility constraint are used as the constraint conditions, and the objective function of the time optimal trajectory generation problem is established; Based on the discretization method, the time-optimal trajectory generation problem is reconstructed into a solvable second-order cone optimization problem, and the second-order cone optimization problem is solved iteratively to obtain the time-optimal mining trajectory. 2. The autonomous excavation operation trajectory generation method according to claim 1, wherein the excavator test platform is equipped with an inclination sensor and an absolute encoder, and the inclination sensor and the absolute encoder are respectively used to measure excavation During the movement of the machine, the angular values of the slewing joints and the boom, stick, and bucket joints change, and the data is collected and processed by the computer, and the trajectory is tracked by the controller. 3. The autonomous excavation operation trajectory generation method according to claim 1, characterized in that the operation characteristics of the skilled operator are analyzed by the skilled operator based on the excavation path generation rules for the excavation task of the skilled operator The topological information of the mining path is obtained. 4. The autonomous excavation operation trajectory generation method according to claim 1, characterized in that, on the excavator test platform, the operation characteristics of the skilled operator are combined to analyze the excavation operation motion, and the excavation path model is obtained, including: On the excavator experimental platform, the operation characteristics of skilled operators are combined to analyze the excavation operation movement, and the topological information of the trajectory in the joint space is obtained; processing the topological information of the trajectory in the joint space by means of timing signal alignment, so that the data lengths in the topological information of the trajectory in the joint space are consistent; performing noise reduction processing on the topological information of the trajectory in the joint space by using a moving average filtering method; Taking the average value of multiple groups of joint space trajectories in the topology information of the trajectories in the joint space to obtain an average mining path; Transform the average mining path into the pose space, use the Douglas-Peucker algorithm to find key passing points, and establish the mining path model. 5. The autonomous excavation operation trajectory generation method according to claim 1, wherein the segmented Bezier curve satisfies the following constraints: Path point constraints to ensure that the trajectory passes through key path points; Boundary value constraints, setting the speed and acceleration values of the excavation operation trajectory at the start and end points of the trajectory to meet the state requirements of the excavation operation; Continuity constraints ensure that the order derivatives of the two connected trajectories are continuous at the breakpoints, and a smooth trajectory is obtained. 6. An autonomous excavation operation trajectory generation system, which is applied to the autonomous excavation operation trajectory generation method described in any one of claims 1-5, characterized in that it comprises: The acquisition module is used to analyze the excavation operation movement by combining the operation characteristics of skilled operators on the excavator experimental platform, and obtain the excavation path model; a representation module for representing mining trajectories by segmented Bezier curves; Establishing a module for establishing the objective function of the time-optimal trajectory generation problem by taking the time of excavation operation movement as the optimization target, and taking the continuity constraint, boundary constraint, and dynamic feasibility constraint as constraint conditions; The processing module is used to reconstruct the time-optimal trajectory generation problem into a solvable second-order cone optimization problem, and iteratively solve the second-order cone optimization problem to obtain the time-optimal mining trajectory.

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