Design method for three-vehicle rigid cooperative control based on ROS

Abstract

The invention discloses a design method for three-vehicle rigid cooperative control based on an ROS. The design method comprises the steps that 1, a hardware system matched with an ROS environment is built; step 2, constructing a communication mechanism between AGVs by using an ROS, and establishing a real-time sharing of information and a rapid transmission channel of an instruction; 3, constructing a rigid cooperative control model among the three AGVs according to the relative position and attitude relation of each AGV; 4, designing a control algorithm based on the rigid cooperative control model, and obtaining the speed information of each AGV; 5, integrating a control algorithm into a control system of each AGV, and obtaining a corresponding ROS node to realize execution of the algorithm; 6, verifying the effectiveness and stability of the control algorithm through a simulation experiment and an actual scene test; through an accurate cooperative control algorithm and a rigid cooperative control model, the three vehicles can keep stable relative positions and attitude relations in the carrying process, and the coordination precision and the overall stability are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of control, and in particular to a design method for three-vehicle rigid cooperative control based on ROS. Background Art

[0002] At present, with the continuous development of AGV technology, multi-AGV collaborative control has become an important research direction in the AGV field. However, the current research on multi-AGV collaborative control mainly focuses on flexible collaboration, that is, each AGV coordinates its own motion trajectory and speed to complete the task together, but they do not form a stable overall structure. In contrast, rigid collaborative control, that is, multiple AGVs move together as a rigid whole, has higher stability and accuracy, and is particularly suitable for application scenarios that require high coordination and stability, such as the handling of heavy equipment.

[0003] At present, although there are some studies on the rigid collaborative control of multiple AGVs, most of these methods are based on specific hardware platforms or control systems and lack versatility and flexibility. In addition, for AGV collaborative tasks in large-scale or complex environments, existing methods often face technical problems such as communication delays, large data processing volume, and insufficient stability. Especially in the application of handling equipment, how to achieve rigid collaborative control between multiple AGVs to ensure that they can handle equipment stably and efficiently as a whole has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The purpose of the present invention is to solve the problem of lack of stable and efficient rigid collaborative solutions in existing robot collaborative control methods, especially when multiple AGVs are required to form a rigid body to perform a handling task, how to ensure the collaborative accuracy, stability and response speed between AGVs.

[0005] To solve the above problems, a control method based on the rigid collaborative model is designed based on the ROS (Robot Operating System) software framework. By precisely controlling the speed of each AGV, they can move collaboratively as a whole to achieve efficient and stable equipment handling.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] A design method for three-vehicle rigid cooperative control based on ROS includes the following steps:

[0008] Step 1: Build a hardware system that matches the ROS environment;

[0009] Step 2: Use ROS to build a communication mechanism between AGVs and establish a channel for real-time information sharing and rapid instruction transmission;

[0010] Step 3: Based on the relative position and posture relationship of each AGV, a rigid collaborative control model between the three AGVs is constructed;

[0011] Step 4: Design a control algorithm based on the rigid collaborative control model to obtain the speed information of each AGV;

[0012] Step 5: Integrate the control algorithm into the control system of each AGV and obtain the corresponding ROS nodes to implement the algorithm execution;

[0013] Step 6: Verify the effectiveness and stability of the control algorithm through simulation experiments and actual scenario tests.

[0014] In the above technical solution, the core components and related protocols of ROS are installed on each AGV, so that the ROS environment configurations of the three AGVs are consistent; in the ROS working environment, the ROS topic mechanism is used to synchronize the real-time information sharing between each AGV; in the ROS working environment, the service mechanism is used to establish a communication link between the three AGVs to realize the transmission and execution of mutual control instructions.

[0015] The control design method of the present invention includes the following four parts:

[0016] 1. System Modeling

[0017] Vehicle dynamics model: Establish the dynamics model of each vehicle and the mathematical model of the formation that needs to be maintained, including state variables such as position and speed.

[0018] Model validation: Verify the accuracy and reliability of the model through experiments or simulations.

[0019] In the present invention, it is necessary to ensure the accuracy of system modeling: modeling is the basis of control algorithm design, and it is necessary to ensure that the model can truly reflect the dynamic characteristics of the vehicle.

[0020] 2. Control Algorithm Design

[0021] Control target definition: Define the target of coordinated control of the three vehicles, i.e., maintain a fixed distance between the queues, the same heading angle, and the centers of the vehicles in a straight line.

[0022] Control strategy selection: Select a suitable control strategy. To avoid overshoot, inertia, delay and other problems that occur in closed-loop control, an open-loop control strategy is adopted. The slave vehicle directly calculates its own speed based on the speed of the master vehicle and the mathematical model of formation maintenance.

[0023] Algorithm simulation: Test the effectiveness of control algorithms in a simulation environment and adjust parameters to optimize performance.

[0024] In the present invention, it is necessary to ensure the real-time performance of the control algorithm: in cooperative control, real-time performance is the key, and the algorithm should be able to respond quickly to changes in vehicle status to ensure safety and stability.

[0025] 3. Implementation of collaborative control strategy

[0026] Information sharing mechanism: Based on the ROS system, an information sharing mechanism between vehicles is designed, which is mainly manifested in the publication and subscription of speed data to ensure real-time and accuracy.

[0027] In the present invention, the reliability of information sharing needs to be ensured: information transmission between vehicles must have high reliability and low latency to ensure the effectiveness of collaborative control.

[0028] 4. System Integration

[0029] Hardware selection: Select appropriate sensors (including IMU, LiDAR, etc.) and actuators (including drivers and motors) for system integration.

[0030] Software Development: Develop control software based on the ROS system, including sensor data processing, control algorithm implementation and vehicle-to-vehicle communication modules.

[0031] System testing and optimization: Conduct system testing in a real environment, collect data for performance evaluation, and optimize control algorithms and system configurations.

[0032] In the present invention, it is necessary to ensure the importance of system testing: ensuring the stability and safety of the system under various conditions through sufficient testing and verification is the key to achieving rigid coordinated control of the three vehicles.

[0033] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0034] Improve coordination accuracy and stability: Through precise collaborative control algorithms and rigid collaborative control models, the three vehicles can maintain a stable relative position and posture relationship during the handling process, significantly improving coordination accuracy and overall stability.

[0035] Reduce communication delay: Utilize the real-time communication mechanism of ROS to reduce the delay of information transmission and improve the response speed between AGVs.

[0036] Improve handling efficiency: Through rigid collaborative control, the three vehicles can efficiently transport equipment as a whole, improving the overall handling efficiency.

[0037] Enhanced versatility and flexibility: The control method proposed in the present invention is versatile and flexible, and can adapt to the collaborative control requirements of multiple AGVs in different scales and different task scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0039] Figure 1 This is the ROS system architecture diagram of three AGVs;

[0040] Figure 2 This is a schematic diagram of the relative positions and formations of the three AGVs;

[0041] Figure 3 Schematic diagram of the three-car trajectory for the experimental simulation;

[0042] Figure 4 It is a schematic diagram of the distance change between the front vehicle and the main vehicle in the experimental simulation;

[0043] Figure 5 It is a schematic diagram of the distance change between the rear vehicle and the main vehicle in the experimental simulation. DETAILED DESCRIPTION

[0044] All features disclosed in this specification, or steps in all methods or processes disclosed, except mutually exclusive features and / or steps, can be combined in any manner.

[0045] Any feature disclosed in this specification (including any additional claims, abstract and drawings), unless otherwise stated, may be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

[0046] The implementation of this embodiment includes the following steps:

[0047] Step 1: Hardware preparation and ROS environment construction

[0048] First, prepare three AGVs with autonomous navigation and driving capabilities, and configure corresponding sensors and actuators, such as lidar, motor drive, etc., to ensure that they can sense the environment and execute control instructions. Then, install the core components and related software packages of ROS on each AGV. This includes ROS Master nodes, communication mechanisms, common tools and libraries, etc. Ensure that the ROS environment configurations of the three AGVs are consistent so that they can communicate and collaborate with each other. The present invention uses the Ubuntu20.04 operating system and installs the corresponding neotic version of ROS.

[0049] Step 2: Establishment of communication and information sharing mechanism

[0050] In the ROS working environment, the communication connection between the three AGVs is established by using the ROS topic and service mechanism, such as Figure 1As shown in the figure, by publishing and subscribing to topics, real-time information sharing between AGVs is realized, including their respective positions, postures, speeds, etc. At the same time, the service mechanism is used to realize the transmission and execution of control instructions.

[0051] Step 3: Construction of rigid collaborative control model

[0052] According to the task requirements, the relative positions and postures of the three AGVs during the handling process are clarified. Based on these relationships, a rigid collaborative control model is constructed. The model defines the connection mode and collaborative motion rules between the AGVs to ensure that they can move as a whole. Figure 2 As shown, the middle AGV is the master vehicle, the front and rear AGVs are slave vehicles, and the centers of the three vehicles are at the geometric center of the master vehicle. The present invention requires the three vehicles to always maintain a vertical formation. According to the formation and the position in the spatial coordinate system, the following mathematical model is established:

[0053] Let (X, Y, θ) be the position of the AGV in the global coordinate system in the current state. From the principle of kinematics, we know that its differential is the velocity of the center of the vehicle body in the global coordinate system. The kinematic formula of the AGV in the global coordinate system can be obtained, which is also the velocity conversion relationship between the vehicle body coordinate system and the global coordinate system, as shown in formula (1).

[0054]

[0055] Where (V X ,V Y ,w Z ) is the speed of AGV in the global coordinate system, (v x ,v y ,w z ) is the speed of the AGV in the body coordinate system.

[0056] Figure 2 (X f ,Y f ) is the position coordinate of the front AGV in the global coordinate system, (X m ,Y m ) is the position coordinate of AGV in the global coordinate system, (X r ,Y r ) is the position coordinate of the AGV in the global coordinate. d is the expected distance between the slave AGV and the master AGV under the collaborative control algorithm. Therefore, the position coordinate of the slave AGV can be regarded as the target position that needs to be reached in the current state to meet the rigid body requirements of the three-car collaborative motion. Its heading angle is the same as the heading angle of the master AGV. Then the relationship between the position coordinate of the slave AGV in the global coordinate and the position coordinate of the master AGV can be obtained.

[0057] The middle AGV is the main AGV, and the front and rear AGVs are slave AGVs.

[0058] The lateral, longitudinal and self-rotational speeds of the front AGV in the global coordinate system are: F_x , v F_y , w F The horizontal, vertical and rotational speeds along the self-coordinate are: v f_x , v f_y , w f .

[0059] The lateral, longitudinal and self-rotational speeds of the AGV in the global coordinate system are: M_x , v M_y , w M The horizontal, vertical and rotational speeds along the self-coordinate are: v m_x , v m_y , w m .

[0060] The lateral, longitudinal and self-rotational speeds of the AGV in the global coordinate system are: R_x , v R_y , w R The horizontal, vertical and rotational speeds along the self-coordinate are: v r_x , v r_y , w r .

[0061] The position coordinate relationship of the front vehicle is:

[0062]

[0063] By deriving equation (2), we can obtain the velocity model of the front AGV (in the global coordinate system):

[0064]

[0065] The position coordinate relationship of the rear vehicle is:

[0066]

[0067] By deriving equation (4), we can get the velocity model of the AGV (in the global coordinate system):

[0068]

[0069] The front and rear vehicle speeds in the global coordinates obtained above are used to obtain the speeds of the front and rear vehicles in their own coordinate systems through formula (1). Formula (6) is the speed of the front vehicle, and formula (7) is the speed of the rear vehicle:

[0070]

[0071]

[0072] Step 4: Rigid cooperative control algorithm development

[0073] Based on the rigid collaborative control model, a collaborative control algorithm is developed. The algorithm obtains the speed information of the master AGV in real time and calculates the speed information of the front and rear slave AGVs. The algorithm adopts a distributed control strategy, and each AGV is independently controlled according to its own status and the received instructions, while maintaining coordination with other AGVs.

[0074] Step 5: Algorithm implementation and integration

[0075] The collaborative control algorithm is integrated into the control system of each AGV, and the corresponding ROS nodes are written to implement the algorithm. Each node is responsible for receiving information from other AGVs, calculating control instructions according to the algorithm, and sending them to the actuator for execution.

[0076] Step 6: System optimization and verification

[0077] Build an experimental environment to conduct joint tests on three AGVs. Verify the effectiveness and stability of the control algorithm through simulation experiments and actual scenario tests.

[0078] The above collaborative control was experimentally verified, and the results are as follows Figure 3 As shown, Figure (a) is the trajectory record of the three vehicles. The middle vehicle (main vehicle) rotates around its own center. The front and rear vehicles calculate their own speeds according to the cooperative control algorithm and move in a fixed formation with the main vehicle. The trajectory of the front vehicle is shown in the upper semicircle in the figure, and the trajectory of the rear vehicle is shown in the lower semicircle. The three vehicles maintain a distance of 1m. Figure (b) shows the change in the distance between the front and rear vehicles and the main vehicle. The results show that the distance is maintained at about 1m, which meets the required formation.

[0079] The present invention is not limited to the above-mentioned specific embodiments, but extends to any new features or any new combination disclosed in this specification, as well as any new method or process steps or any new combination disclosed.

Claims

1. A design method for three-vehicle rigid cooperative control based on ROS, characterized in that The design process includes: system modeling, control algorithm design, collaborative control strategy implementation, and system integration.

2. According to claim 1, a design method for three-vehicle rigid cooperative control based on ROS is characterized in that The following steps are involved: Step 1: Build a hardware system that matches the ROS environment; Step 2: Use ROS to build a communication mechanism between AGVs and establish a channel for real-time information sharing and rapid instruction transmission; Step 3: Based on the relative position and posture relationship of each AGV, a rigid collaborative control model between the three AGVs is constructed; Step 4: Design a control algorithm based on the rigid collaborative control model to obtain the speed information of each AGV; Step 5: Integrate the control algorithm into the control system of each AGV and obtain the corresponding ROS nodes to implement the algorithm execution; Step 6: Verify the effectiveness and stability of the control algorithm through simulation experiments and actual scenario tests.

3. The design method of three-vehicle rigid cooperative control based on ROS according to claim 2 is characterized in that: Install ROS core components and related protocols on each AGV to ensure that the ROS environment configuration of the three AGVs is consistent; In the ROS working environment, the ROS topic mechanism is used to synchronize the real-time information sharing between each AGV; In the ROS working environment, the service mechanism is used to establish a communication link between the three AGVs to achieve the transmission and execution of mutual control instructions.

4. The design method of three-vehicle rigid cooperative control based on ROS according to claim 3 is characterized by: The three AGVs are arranged in a straight line formation, and the center of the three AGVs is at the geometric center of the middle AGV. The motion control model of the three AGVs is: Where: (X, Y, θ) is the position of the AGV in the global coordinate system in the current state, (V x ,V y ,W z ) is the speed of AGV in the global coordinate system, (v x ,v y ,w z ) is the speed of the AGV in the body coordinate system.

5. The design method of three-vehicle rigid cooperative control based on ROS according to claim 3 is characterized by: A distributed control strategy is adopted to independently control the instructions received by each AGV and maintain coordination with other AGVs.

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