Five-degree-of-freedom industrial robot path planning method and system based on D-H parameter and dynamics modeling

Abstract

The invention relates to the technical field of industrial robots, in particular to a five-degree-of-freedom industrial robot path planning method and system based on D-H parameters and dynamics modeling, and realizes high-precision path planning and dynamic environment adaptation by combining kinematics modeling, dynamics analysis and MATLAB simulation technologies. The method comprises the steps of building a robot kinematics model, building a kinetic equation, mixing a path planning strategy, solving inverse kinematics and performing multi-sensor fusion control. The system covers modeling, calculation, planning, simulation and feedback modules, and the operation efficiency and safety of the industrial robot in a complex scene are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robots, and in particular to a path planning method and system for a five-degree-of-freedom industrial robot based on D-H parameters and dynamic modeling. Background Art

[0002] Industrial robots generally refer to multi-joint manipulators or multi-degree-of-freedom machine devices used in the industrial field. For each production field, industrial robots are a new generation of tools that can extend people's physical and intellectual capabilities. When an industrial robot moves, it requires a suitable trajectory to avoid collisions with other objects and pass through predetermined points in space coordinates, so as to achieve fast and accurate movement. Robot trajectory planning is to study the robot trajectory generation algorithm based on kinematics. In the process of industrial robot trajectory planning, first, we need to consider some motion state variables of the end effector of the industrial robot, such as: spatial position, attitude, spatial movement speed, and acceleration, etc. Secondly, we need to consider the safety, efficiency, and accuracy of the algorithm. A perfect trajectory planning algorithm should be able to meet the characteristics of a small amount of calculation, various trajectory planning curves, and safety.

[0003] The existing industrial robot path planning technologies mostly adopt traditional kinematic analysis methods, and there are the following problems:

[0004] 1. Insufficient model accuracy: The traditional method does not fully combine the D-H parameter method to establish an accurate model of a multi-degree-of-freedom robot, resulting in a large path planning error.

[0005] 2. Poor dynamic adaptability: Most solutions do not integrate dynamic analysis and are difficult to meet the stability requirements under high-speed movement or load changes.

[0006] 3. Low simulation efficiency: There is a lack of an efficient simulation tool to verify the path planning algorithm, resulting in a long development cycle and high cost.

[0007] Therefore, there is an urgent need for an intelligent path planning method that combines accurate modeling, dynamic analysis, and efficient simulation. Summary of the Invention

[0008] To solve the above technical problems.

[0009] The present application provides a path planning method for a five-degree-of-freedom industrial robot based on D-H parameters and dynamic modeling, including the following steps:

[0010] S1: Construct a three-dimensional kinematic model of a five-degree-of-freedom robot by the D-H parameter method, and determine the joint coordinate system and link parameters;

[0011] S2: Establish a robot dynamic model based on the Lagrange equation, and calculate the mapping relationship between the joint driving torque and the motion trajectory;

[0012] S3: Adopt a hybrid strategy combining global path planning and local path planning to generate a collision-free optimal path;

[0013] S4: Use MATLAB for inverse kinematics simulation to solve the joint angle sequence corresponding to the target pose;

[0014] S5: Real-time correct the path deviation through multi-sensor information fusion to achieve trajectory tracking control in a dynamic environment.

[0015] Furthermore, in the D-H parameter method, each joint coordinate system is established based on the structural characteristics of the five-degree-of-freedom robot, including the base, waist, upper arm, forearm, wrist, and hand. A revolute pair is formed between the base and the waist, a revolute pair is formed between the waist and the upper arm, a revolute pair is formed between the upper arm and the forearm, a revolute pair is formed between the forearm and the wrist, and a revolute pair is formed between the wrist and the hand.

[0016] Furthermore, the dynamic modeling specifically includes:

[0017] Calculate the kinetic energy and potential energy of each link through the pseudo-inertia matrix; Derive the dynamic equation of the joint torque and motion parameters based on the Lagrangian function; Introduce the inertia compensation term of the drive element to optimize the real-time performance of the dynamic model.

[0018] Furthermore, the global path planning uses the RRT algorithm to generate the initial path, and the local path planning adjusts the joint motion parameters in real time based on the PID controller and Kalman filter.

[0019] Furthermore, the inverse kinematics simulation is implemented through the Robotics Toolbox of MATLAB, specifically including: calling the ikine function to solve the joint angle vector of the target pose; using the jtraj and ctraj functions for trajectory interpolation in the joint space and Cartesian space; verifying the uniqueness and feasibility of the inverse solution to avoid singular configurations.

[0020] Furthermore, the multi-sensor information fusion includes a force sensor, a vision sensor, and an inertial measurement unit, and the fusion algorithm uses Bayesian estimation or neural network to enhance the robustness of path tracking.

[0021] Furthermore, a five-degree-of-freedom industrial robot path planning system based on D-H parameters and dynamic modeling includes:

[0022] A kinematic modeling module for defining the robot structure through the D-H parameter method;

[0023] A dynamic calculation module that outputs the joint driving torque in real time based on the Lagrangian equation;

[0024] The path planning module integrates global and local planning algorithms and generates trajectory instructions;

[0025] The simulation verification module realizes inverse kinematics solution and dynamic simulation through MATLAB;

[0026] The sensor feedback module collects environmental data in real time and corrects path deviations.

[0027] Furthermore, the path planning module supports offline programming and online adjustment, receives task instructions through an external control interface, and outputs a joint angle sequence to the servo drive system.

[0028] The beneficial effects of the present invention compared with the prior art are:

[0029] 1. This application combines kinematic modeling, dynamic analysis, and MATLAB simulation technology to achieve high-precision path planning and dynamic environment adaptation. The method includes constructing a robot kinematic model, establishing a dynamic equation, a hybrid path planning strategy, inverse kinematics solution, and multi-sensor fusion control. The system covers modeling, calculation, planning, simulation, and feedback modules, effectively improving the operation efficiency and safety of industrial robots in complex scenarios.

[0030] 2. This application constructs an accurate robot model by improving the D-H parameter method, optimizes joint pose calculation by combining homogeneous transformation matrices, and reduces the error rate; by integrating a dynamic analysis module, it calculates joint torques and inertia tensors in real time to ensure anti-interference ability under high-speed motion. Fast simulation is realized based on the Robotics Toolbox of MATLAB, supporting double path planning verification in Cartesian space and joint space, further shortening the development cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a flowchart of the steps of the path planning method of the present invention;

[0032] Figure 2 is a three-dimensional structure schematic diagram of the industrial robot of the present invention;

[0033] Figure 3 is a structural diagram of the path planning system of the present invention;

[0034] Figure 4 is a schematic diagram of establishing the D-H coordinate system of the mobile joint link of the present invention;

[0035] Figure 5 is a computer simulation diagram of the five-degree-of-freedom manipulator of the present invention;

[0036] Figure 6 is a Matlab simulation diagram of the motion trajectory of the end effector of the present invention.

[0037] The reference numerals in the figure are: industrial robot - 1; base - 11; waist - 12; upper arm - 13; forearm - 14; wrist - 15; hand - 16, kinematic modeling module - 21; dynamic calculation module - 22; path planning module - 23; simulation verification module - 24; sensor feedback module - 25. Detailed implementation manners

[0038] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and other obvious variations can be thought of by those skilled in the art.

[0039] As Figures 1 to 3 shown:

[0040] A path planning method for a five - degree - of - freedom industrial robot based on D - H parameters and dynamic modeling, comprising the following steps:

[0041] S1: Construct a three - dimensional kinematic model of the five - degree - of - freedom robot by the D - H parameter method, and determine the joint coordinate systems and link parameters;

[0042] S2: Establish a dynamic model of the robot based on the Lagrange equation, and calculate the mapping relationship between the joint driving torque and the motion trajectory;

[0043] S3: Adopt a hybrid strategy combining global path planning and local path planning to generate a collision - free optimal path;

[0044] S4: Use MATLAB for inverse kinematics simulation to solve the joint angle sequence corresponding to the target pose;

[0045] S5: Real - time correct the path deviation through multi - sensor information fusion to achieve trajectory tracking control in a dynamic environment.

[0046] Using the above steps, complete the path planning of the five - degree - of - freedom industrial robot in sequence, establish a three - dimensional solid model of the five - degree - of - freedom robot using the D - H parameter method, and analyze its kinematic characteristics. Conduct kinematic simulation through MATLAB, optimize the path planning algorithm, and improve the efficiency and accuracy of path planning. Combine dynamic analysis to ensure the stability and load - carrying capacity of the robot during the path planning process.

[0047] In the D - H parameter method, each joint coordinate system is established based on the structural characteristics of the five - degree - of - freedom robot, including the base 11, waist 12, upper arm 13, forearm 14, wrist 15 and hand 16. A revolute pair is formed between the base 11 and the waist 12, a rotational pair is formed between the waist 12 and the upper arm 13, a rotational pair is formed between the upper arm 13 and the forearm 14, a rotational pair is formed between the forearm 14 and the wrist 15, and a revolute pair is formed between the wrist 15 and the hand 16.

[0048] When establishing a 3D robot model based on the D-H parameter method, the D-H parameter table is defined to include the link length (ai), the link twist angle (α i ), the joint rotation angle (θ i ), and the joint offset (d i ); the pose matrix of the end effector is derived through the homogeneous transformation matrix, and a 3D model is generated in combination with MATLAB.

[0049] When performing dynamic modeling, the kinetic energy and potential energy of each link are calculated through the pseudo-inertia matrix; the dynamic equations of the joint torque and motion parameters are derived based on the Lagrangian function; the inertia compensation term of the drive element is introduced to optimize the real-time performance of the dynamic model.

[0050] According to the Lagrangian equation:

[0051] For i = 1, 2,..., n;

[0052]

[0053] Calculate the joint driving torque, and optimize the dynamic load distribution in path planning in combination with the pseudo-inertia matrix.

[0054] For global path planning, the RRT algorithm is used to generate the initial path, and the local path planning is based on the PID controller and Kalman filter to adjust the joint motion parameters in real time.

[0055] The inverse kinematics simulation is implemented through the Robotics Toolbox of MATLAB, specifically including: calling the ikine function to solve the joint angle vector of the target pose; using the jtraj and ctraj functions for trajectory interpolation in the joint space and Cartesian space; verifying the uniqueness and feasibility of the inverse solution to avoid singular configurations.

[0056] Use Matlab to simulate the motion trajectory of the end effector of the manipulator: The ctraj and jtraj functions provided by the Robotics Toolbox can be used to achieve Cartesian planning and joint space planning. The calling format of the ctraj function is as follows:

[0057] TC = CTRAJ(T0, T1, R)

[0058] The above indicates that the parameter TC is the Cartesian planning trajectory from T0 to T1, and R is the given path distance vector. Each value of R must be between 0 and 1.

[0059] The calling format of the jtraj function is as follows:

[0060] [Q, QD, QDD] = JTRAJ(Q0, Q1, T)

[0061] The parameter Q is the joint space planned trajectory from state Q0 to Q1, N is the number of planned points, and T is the length of the given time vector. QD and QDD are the velocity and acceleration of the returned planned trajectory. Simulation analysis is carried out based on the displayed data. The trajectory tracking error under high-speed motion is verified through MATLAB simulation.

[0062] By fusing the information of multiple sensors, such as force sensors, vision sensors and inertial measurement units, the fusion algorithm adopts Bayesian estimation or neural network to improve the robustness of path tracking. Combining with Lagrangian dynamics equation to analyze the relationship between robot load and joint driving force, ensuring the dynamic stability of path planning; Using inverse kinematics algorithm and Kalman filtering technology to realize adaptive path tracking control in complex environment.

[0063] Such as Figure 4 As shown, a five-degree-of-freedom industrial robot path planning system based on D-H parameters and dynamics modeling provided by the present invention includes:

[0064] A kinematic modeling module for defining the robot structure by D-H parameter method;

[0065] A dynamics calculation module for real-time output of joint driving torque based on Lagrangian equation;

[0066] A path planning module integrating global and local planning algorithms and generating trajectory instructions;

[0067] A simulation verification module for realizing inverse kinematics solution and dynamic simulation through MATLAB;

[0068] A sensor feedback module for real-time collecting environmental data and correcting path deviation.

[0069] The path planning module supports offline programming and online adjustment, receives task instructions through an external control interface, and outputs a joint angle sequence to the servo drive system.

[0070] This system analyzes the basic model and theory of industrial robots through kinematic modeling and dynamics calculation, generates trajectories and completes path planning by integrating global and local planning algorithms. At the same time, inverse kinematics solution and dynamic simulation are realized through MATLAB, and path tracking control based on inverse kinematics is realized. Finally, the environmental data information collected by multiple groups of sensors is fused to correct path deviation in real time.

[0071] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, various changes and improvements will occur to the present invention, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A path planning method for a five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling, characterized in that, It includes the following steps: S1: Construct a three-dimensional kinematic model of a five-degree-of-freedom robot by the D-H parameter method, and determine the joint coordinate systems and link parameters; S2: Establish a robot dynamics model based on the Lagrange equation, and calculate the mapping relationship between the joint driving torque and the motion trajectory; S3: Adopt a hybrid strategy combining global path planning and local path planning to generate a collision-free optimal path; S4: Use MATLAB for inverse kinematics simulation to solve the joint angle sequence corresponding to the target pose; S5: Real-time correct the path deviation through multi-sensor information fusion to achieve trajectory tracking control in a dynamic environment.

2. The path planning method of the five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 1, wherein In the D-H parameter method, each joint coordinate system is established based on the structural characteristics of the five-degree-of-freedom robot (1), including the base (11), waist (12), large arm (13), small arm (14), wrist (15) and hand (16). The base (11) and the waist (12) form a revolute pair, the waist (12) and the large arm (13) form a rotational pair, the large arm (13) and the small arm (14) form a rotational pair, the small arm (14) and the wrist (15) form a rotational pair, and the wrist (15) and the hand (16) form a revolute pair.

3. The path planning method for a five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 1, characterized in that, The specific dynamics modeling includes: Calculate the kinetic energy and potential energy of each link through the pseudo-inertia matrix; Derive the dynamic equation of the joint torque and motion parameters based on the Lagrangian function; Introduce the inertia compensation term of the drive element to optimize the real-time performance of the dynamics model.

4. The path planning method of the five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 1, wherein The global path planning uses the RRT algorithm to generate an initial path, and the local path planning is based on the PID controller and the Kalman filter to adjust the joint motion parameters in real time.

5. The path planning method of a five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 1, characterized in that The inverse kinematics simulation is realized through the Robotics Toolbox of MATLAB, and specifically includes: calling the ikine function to solve the joint angle vector of the target pose; Using the jtraj and ctraj functions for trajectory interpolation in the joint space and the Cartesian space; Verify the uniqueness and feasibility of the inverse solution to avoid singular configurations.

6. The path planning method of a five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 1, characterized in that, The multi-sensor information fusion includes a force sensor, a vision sensor and an inertial measurement unit, and the fusion algorithm uses Bayesian estimation or neural network to improve the robustness of path tracking.

7. A five-degree-of-freedom industrial robot path planning system based on D-H parameters and kinematic modeling, characterized in that, It includes: A kinematic modeling module for defining the robot structure by the D-H parameter method; A dynamics calculation module that outputs the joint driving torque in real time based on the Lagrange equation; A path planning module that integrates global and local planning algorithms and generates trajectory instructions; A simulation verification module that realizes inverse kinematics solution and dynamic simulation through MATLAB; A sensor feedback module that collects environmental data in real time and corrects the path deviation.

8. The path planning system of the five-degree-of-freedom industrial robot based on D-H parameters and kinematic modeling according to claim 7, characterized in that The path planning module supports offline programming and online adjustment, receives task instructions through an external control interface, and outputs the joint angle sequence to the servo drive system.

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