A method and system for automatic assisted berthing of ships based on laser ranging

Abstract

The invention relates to the technical field of automatic assisted berthing of ships, and specifically discloses a method and system for automatic assisted berthing of ships based on laser ranging. The method collects environmental data and position information between a ship and a berth in real time, utilizes the environmental data and dynamic information of the ship, generates an optimal berthing path and performs path accuracy evaluation, and dynamically calculates a correction coefficient using a Bayesian network algorithm for path deviations caused by environmental interference, reflectivity changes and multi-path reflection factors, thereby correcting the heading, speed and attitude of the ship to ensure that the ship can dock with the berth accurately and safely. Through path correction and updating, the dynamic behavior of the ship is adjusted in real time to adapt to changes in environmental factors and avoid potential obstacles and risks. By accurately controlling the relative position between the ship and the berth, the ship is ensured to dock accurately and avoid collision risks during the berthing process.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic assisted berthing of ships, and in particular to a method and system for automatic assisted berthing of ships based on laser ranging. Background Art

[0002] With the development of ship automation technology, automatic assisted berthing systems have been widely used to improve the accuracy of ship berthing and reduce the risks of human operation. Traditional ship berthing operations rely on the operation and judgment of the crew and are easily affected by environmental factors such as waves, wind speed, and light changes, which lead to safety hazards and increased operational difficulty during berthing. In order to meet these challenges, modern automatic berthing systems use multi-sensor fusion technology, combined with laser ranging, ultrasonic sensors, and visual cameras, to achieve real-time data collection and path planning between ships and berths.

[0003] The prior art has the following deficiencies:

[0004] Existing automatic assisted berthing systems usually fail to fully consider the impact of environmental interference and reflectivity changes on path planning. Under complex environmental conditions, such as multipath effects or dynamic obstacles around the ship, path deviations and ranging errors will occur. Path planning in the prior art mostly relies on fixed models or simple correction algorithms, and cannot be flexibly adjusted according to real-time environmental changes and dynamic behaviors of the ship, thereby affecting berthing accuracy and operational safety. In order to solve these problems, the present invention introduces a correction coefficient calculation method based on a Bayesian network. By comprehensively considering the ship's heading, speed and interference coefficient, the path planning can be dynamically adjusted, and environmental interference can be corrected in real time, thereby improving the adaptability, accuracy and safety of the automatic berthing system. Summary of the invention

[0005] The object of the present invention is to provide a method and system for automatic assisted berthing of a ship based on laser ranging to solve the above-mentioned problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for automatically assisting a ship in berthing based on laser ranging comprises the following steps:

[0008] S1: Use laser ranging equipment, ultrasonic sensors and visual cameras to synchronously collect environmental data and location information between the ship and the berth;

[0009] The environmental data includes the berth edge position, the dock obstacle position and relative distance information, and the position information includes the current position, heading angle and speed status of the vessel;

[0010] S2: Generate a berthing path using the berthing model and the dynamic model based on the collected environmental data and the current position of the vessel, evaluate the accuracy of the generated berthing path, and predict the potential deviation range of the path;

[0011] S3: Based on the deviated ship path, analyze whether the path deviation is due to the reflectivity change of the laser signal and the influence of multipath reflection on the ranging data, and evaluate the influence of reflectivity and environmental interference on the accuracy of path planning;

[0012] S4: Based on the evaluation results, the path is corrected, the path planning model is updated, the optimal path between the ship and the berth is recalculated, and the ship's heading and speed are adjusted to ensure that the new path is accurate and avoids environmental interference;

[0013] S5: According to the corrected path and changes in environmental factors, the dynamic behavior of the ship is adjusted in real time to optimize the relative position and posture between the ship and the berth. By updating the path, it is ensured that the ship can dock safely and accurately at the berth.

[0014] As a further solution of the present invention: the accuracy assessment of the generated berthing path and the prediction of the potential deviation range of the path specifically include:

[0015] The collected environmental data is integrated with the current position, heading angle and speed state of the ship, and the berth model including the berth edge and berth space shape and the ship's dynamic model is combined to calculate the optimal path from the current position of the ship to the berth;

[0016] Based on the berth model and the dynamic model, combined with the current navigation status of the ship including speed and direction, a preliminary berthing path is generated, which includes each position point, heading and speed information of the ship;

[0017] By comparing the generated path with the actual trajectory of the ship, the path deviation coefficient is calculated;

[0018] The path deviation coefficient calculates the path deviation by analyzing the distance error between each point on the path and the actual ship position, and evaluates the accuracy of the ship during the berthing process;

[0019] The deviation of the vessel's berthing path is evaluated by calculating the path deviation coefficient.

[0020] As a further solution of the present invention: the process of obtaining the path deviation coefficient is:

[0021] Get the ship's heading angle, speed and two-dimensional coordinates, and construct the state vector ;

[0022] in, ;

[0023] In the formula, and Represents the two-dimensional coordinates of the ship at its current position, Indicates the heading angle of the ship. Indicates the speed of the ship, Represents each time point of data collection;

[0024] According to the dynamic model of the ship, the state transfer equation is established to describe the motion state of the ship. The calculation expression is:

[0025] ;

[0026] In the formula, represents the state transfer matrix, represents the control input matrix, represents the control input, represents process noise;

[0027] Based on the environmental sensor data, a measurement model is established, and the calculation expression is:

[0028] ;

[0029] In the formula, Indicates the actual position of the vessel, represents the measurement matrix, represents the observation noise;

[0030] Perform Kalman filter prediction and update to obtain the estimated state of the ship ;

[0031] The steps of the prediction are:

[0032] ;

[0033] ;

[0034] The updating steps are:

[0035] ;

[0036] ;

[0037] ;

[0038] in, represents the Kalman gain, represents the observation noise covariance matrix, represents the process noise covariance matrix, represents the estimation error covariance matrix, represents the prediction error covariance matrix;

[0039] At each time step, the Kalman filter will give the predicted value of the current position coordinates of the ship, obtain the actual observed value of the ship's position coordinates, and calculate the deviation value between the predicted position and the actual position. The calculation expression is:

[0040] ;

[0041] In the formula, Indicates The deviation value at each time point, and Represents the predicted value of the current position coordinates, and The coordinates of the ship's position representing the actual observations;

[0042] The deviation measure of the entire berthing path is obtained by accumulating the deviation value at each time point, which is recorded as the path deviation coefficient. The calculation expression is:

[0043] ;

[0044] In the formula, represents the path deviation coefficient, Indicates the total number of time points.

[0045] As a further solution of the present invention: the evaluation of the influence of reflectivity and environmental interference on the accuracy of path planning specifically includes:

[0046] By real-time monitoring of the intensity changes of the reflected signal obtained by the laser ranging equipment, the changes in the laser signal during reflection are analyzed;

[0047] When the laser signal reflects off multiple surfaces and returns to the ranging device, multiple reflection paths are generated, and these paths have different lengths, resulting in the received signal containing multiple reflection sources;

[0048] Analyze multipath reflections, compare the time delay difference between multipath reflections and direct path reflections, and identify ranging errors caused by multipath effects;

[0049] Based on the analysis results of reflectivity changes and multipath reflections, the interference index is calculated. According to the calculated interference index, the specific impact of reflectivity and environmental interference on the accuracy of path planning is evaluated.

[0050] As a further solution of the present invention: the process of obtaining the interference index is:

[0051] The interference index is calculated by particle filtering, including:

[0052] Initialize the particle swarm, which consists of particles, each particle represents an interference state, and the particle set , where each particle The state vector includes:

[0053] : No. The reflectivity of each particle indicates the reflection intensity of the laser signal;

[0054] : No. The time delay of each particle represents the signal propagation delay caused by multipath reflections;

[0055] : No. The state vector of each particle contains the position and speed information of the ship;

[0056] in, represents a particle in a particle group, represents the total number of particles;

[0057] At each time step, particle prediction is performed based on the particle state transition model, and the predicted state of each particle is calculated. The calculation expression is:

[0058] ;

[0059] in, The transfer function represents the state of the particle, which predicts the state at the current moment based on the state at the previous moment;

[0060] represents process noise;

[0061] According to the real-time acquired reflection signal data, the particle weight is updated and the Weight , the calculation expression is:

[0062] ;

[0063] in, For particles At the moment The probability of measurement under Represents particles At the moment The weight of

[0064] Resample the particle swarm and regenerate the particle set ;

[0065] in, Indicates the moment of each collection;

[0066] Based on the updated particle set, the interference index is calculated, and the calculation expression is:

[0067] ;

[0068] In the formula, represents the interference index, Indicates The deviation between the reflectivity and time delay of each particle and the actual value is calculated as:

[0069] ;

[0070] In the formula, represents the actual measured reflectivity, represents the actual measured time delay;

[0071] Based on the calculated interference index, the influence of reflectivity and environmental interference on the accuracy of path planning is evaluated.

[0072] As a further solution of the present invention: the path correction according to the evaluation result specifically includes:

[0073] According to the specific impact of reflectivity and environmental interference on the accuracy of path planning, combined with the interference coefficient and the heading and speed of the ship, the correction coefficient is comprehensively calculated for path correction and update.

[0074] As a further solution of the present invention: the process of obtaining the correction coefficient is:

[0075] The Bayesian network is used to calculate the correction factor, including:

[0076] Input variables include: speed, heading and disturbance coefficient;

[0077] Target variable: correction factor;

[0078] Set the dependency between input variables and target variables as conditional probabilities;

[0079] Constructing a conditional probability table, including: defining a prior distribution of a prior probability correction coefficient, which represents the distribution of the correction coefficient without any observed data;

[0080] Define conditional probability, given the speed and heading information, and predict the impact of reflectivity and environmental interference on the correction factor;

[0081] The posterior probability distribution of the correction coefficient is calculated using Bayes' theorem, and the calculation expression is:

[0082] ;

[0083] in, represents the prior probability of the correction coefficient, represents the conditional probability of ship speed under a given correction factor, represents the conditional probability of the heading angle under a given correction factor, represents the conditional probability of the interference coefficient under a given correction factor;

[0084] The posterior probability of the correction coefficient is calculated by the Bayesian inference algorithm. According to the posterior probability of the correction coefficient, the correction coefficient is calculated. The calculation expression is:

[0085] ;

[0086] in, represents the calculated correction factor, Indicates the current speed of the ship. Indicates the current heading of the ship. Indicates the current interference coefficient of the ship;

[0087] The calculated correction coefficient is applied to path correction, and the corrected path calculation expression is:

[0088] ;

[0089] In the formula, represents the corrected path, Represents the original path, Indicates the increment of the path correction.

[0090] A laser ranging-based automatic auxiliary berthing system for ships, comprising:

[0091] A data acquisition module, wherein the data acquisition module uses a laser rangefinder, an ultrasonic sensor, and a visual camera to synchronously collect environmental data and location information between the vessel and the berth;

[0092] A path deviation assessment module, which generates a berthing path using a berthing model and a dynamic model based on the collected environmental data and the current position of the vessel, assesses the accuracy of the generated berthing path, and predicts the potential deviation range of the path;

[0093] An interference assessment module, which analyzes, based on the deviated ship path, whether the path deviation is due to the influence of reflectivity change of the laser signal and multipath reflection on the ranging data, and assesses the influence of reflectivity and environmental interference on the accuracy of path planning;

[0094] A path correction and vessel adjustment module, which corrects the path according to the evaluation results, updates the path planning model, recalculates the optimal path between the vessel and the berth, adjusts the course and speed of the vessel, ensures that the new path is accurate, and avoids environmental interference;

[0095] A path updating module adjusts the dynamic behavior of the vessel in real time according to the corrected path and changes in environmental factors, optimizes the relative position and posture between the vessel and the berth, and ensures that the vessel can dock with the berth safely and accurately by updating the path.

[0096] Beneficial effects of the present invention:

[0097] (1) The present invention uses data fusion technology of multiple sensors such as laser ranging, ultrasonic sensors and visual cameras to monitor environmental changes in real time during the berthing process and accurately evaluate the deviation between the ship and the berth. The system uses the path deviation coefficient evaluation method, combined with the real-time acquired environmental data and ship status information, to dynamically adjust the berthing path to ensure high accuracy of path planning under various interference conditions. The laser ranging equipment provides high-precision distance measurement and can make timely path corrections under the influence of water surface reflection and multipath effects. The ultrasonic sensor helps detect close-range obstacles, further ensuring the precise docking of ships in complex and dynamic environments. Through this multi-level sensor fusion and path correction mechanism, the present invention significantly improves the accuracy of ship berthing operations, minimizes collisions or deviations caused by environmental interference, obstacles and potential risks, and improves the safety and reliability of berthing operations.

[0098] (2) The Bayesian network correction coefficient calculation method introduced in the present invention can accurately predict and correct the ship's path in real time in a complex environment. Taking into account environmental interference factors, the system dynamically adjusts the path planning through a comprehensive analysis of the heading, speed and interference coefficient. The Bayesian network uses conditional probability and prior knowledge to flexibly respond to environmental changes, such as the fluctuation of reflectivity and the impact of multipath effects on ranging data, and updates the path correction coefficient in real time. As the environmental interference continues to change during the berthing process of the ship, the Bayesian network can continuously optimize the path planning based on the dynamic behavior of the current ship, combined with environmental data and real-time feedback, thereby ensuring that the ship can accurately avoid obstacles and eliminate potential deviations and collision risks. This correction and adjustment mechanism based on interference makes the ship highly adaptable and robust in complex and changing environments, further improves the flexibility, efficiency and safety of the automatic berthing process, and ensures the high-precision execution of path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] The present invention will be further described below in conjunction with the accompanying drawings.

[0100] Figure 1 It is a flowchart of the specific steps of a method for automatic assisted berthing of a ship based on laser ranging of the present invention;

[0101] Figure 2 The present invention is a flowchart of a laser ranging-based ship automatic auxiliary berthing system. DETAILED DESCRIPTION

[0102] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0103] See also Figure 1 As shown, the present invention is a method for automatically assisting a ship to berth based on laser ranging, comprising the following steps:

[0104] S1: Use laser ranging equipment, ultrasonic sensors and visual cameras to synchronously collect environmental data and location information between the ship and the berth;

[0105] The environmental data includes the berth edge position, the dock obstacle position and relative distance information, and the position information includes the current position, heading angle and speed status of the vessel;

[0106] S2: Generate a berthing path using the berthing model and the dynamic model based on the collected environmental data and the current position of the vessel, evaluate the accuracy of the generated berthing path, and predict the potential deviation range of the path;

[0107] S3: Based on the deviated ship path, analyze whether the path deviation is due to the reflectivity change of the laser signal and the influence of multipath reflection on the ranging data;

[0108] Evaluate the impact of reflectivity and environmental interference on path planning accuracy, calculate the interference index, and evaluate the degree of interference factors on path accuracy;

[0109] S4: Based on the evaluation results, the path is corrected, the path planning model is updated, the optimal path between the ship and the berth is recalculated, and the heading, speed and attitude are adjusted to ensure that the new path is accurate and avoids environmental interference;

[0110] S5: According to the corrected path and changes in environmental factors, the dynamic behavior of the ship is adjusted in real time to optimize the relative position and posture between the ship and the berth. By continuously updating the path, the ship is ensured to dock safely and accurately at the berth.

[0111] In S1, laser ranging equipment, ultrasonic sensors and visual cameras are used to synchronously collect environmental data and location information between the ship and the berth, including:

[0112] Laser ranging equipment is used to accurately obtain the distance information between the ship and the berth, including: the distance of the berth edge, the dock obstacles and the water surface reflection data;

[0113] When the laser ranging signal is reflected back to the receiver, the device calculates the return time and signal strength to obtain the precise location and environmental characteristics of the berth;

[0114] Ultrasonic sensors provide short-range obstacle detection, helping to monitor dynamic obstacles and irregular environmental changes around the vessel in real time, such as water surface fluctuations;

[0115] The visual camera captures environmental images to assist in identifying the morphological features of the berth and surrounding obstacles, ensuring the comprehensiveness and accuracy of data collection;

[0116] The vessel’s position information is obtained in real time through the Global Positioning System (GPS) and Inertial Measurement Unit (IMU);

[0117] The GPS system provides the precise geographic location of the vessel, while the IMU is used to track the vessel's heading angle and speed. By combining these two types of information, the system can dynamically monitor the vessel's trajectory. During the multi-sensor data fusion process, the vessel's speed, heading, and relative position to the berth are updated in real time to ensure that the relative relationship between the vessel and the berth is accurately reflected in a dynamic environment;

[0118] By integrating sensor data, the system is able to build an accurate environmental model, providing a reliable basis for subsequent path planning and adjustment.

[0119] In S2, based on the collected environmental data and the current position of the vessel, the berthing path is generated using the berthing model and the dynamic model. The accuracy of the generated berthing path is evaluated and the potential deviation range of the path is predicted, including:

[0120] The collected environmental data is integrated with the current position, heading angle and speed state of the ship, and the berth model including the berth edge and berth space shape and the ship's dynamic model is combined to calculate the optimal path from the current position of the ship to the berth;

[0121] Based on the berth model and the dynamic model, combined with the current navigation status of the ship including speed and direction, a preliminary berthing path is generated, which includes each position point, heading and speed information of the ship;

[0122] By comparing the generated path with the actual trajectory of the ship, the path deviation coefficient is calculated;

[0123] The path deviation coefficient calculates the path deviation by analyzing the distance error between each point on the path and the actual ship position, and evaluates the accuracy of the ship during the berthing process;

[0124] The deviation of the vessel's berthing path is evaluated by calculating the path deviation coefficient;

[0125] The process of obtaining the path deviation coefficient is as follows:

[0126] Get the ship's heading angle, speed and two-dimensional coordinates, and construct the state vector ;

[0127] in, ;

[0128] In the formula, and Represents the two-dimensional coordinates of the ship at its current position, Indicates the heading angle of the ship. Indicates the speed of the ship, Represents each time point of data collection;

[0129] According to the dynamic model of the ship, the state transfer equation is established to describe the motion state of the ship. The calculation expression is:

[0130] ;

[0131] In the formula, represents the state transfer matrix, represents the control input matrix, represents the control input, represents process noise;

[0132] Based on the environmental sensor data, a measurement model is established, and the calculation expression is:

[0133] ;

[0134] In the formula, Indicates the actual position of the vessel, represents the measurement matrix, represents the observation noise;

[0135] Perform Kalman filter prediction and update to obtain the estimated state of the ship ;

[0136] The steps of the prediction are:

[0137] ;

[0138] ;

[0139] The updating steps are:

[0140] ;

[0141] ;

[0142] ;

[0143] in, represents the Kalman gain, represents the observation noise covariance matrix, represents the process noise covariance matrix, represents the estimation error covariance matrix, represents the prediction error covariance matrix;

[0144] At each time step, the Kalman filter will give the predicted value of the current position coordinates of the ship, obtain the actual observed value of the ship's position coordinates, and calculate the deviation value between the predicted position and the actual position. The calculation expression is:

[0145] ;

[0146] In the formula, Indicates The deviation value at each time point, and Represents the predicted value of the current position coordinates, and The coordinates of the ship's position representing the actual observations;

[0147] The deviation measure of the entire berthing path is obtained by accumulating the deviation value at each time point, which is recorded as the path deviation coefficient. The calculation expression is:

[0148] ;

[0149] In the formula, represents the path deviation coefficient, Indicates the total number of time points;

[0150] The path deviation coefficient of each vessel is compared with a preset threshold;

[0151] If the path deviation coefficient is greater than or equal to the preset threshold, it means that the corresponding ship has a high degree of berthing deviation;

[0152] If the path deviation coefficient is less than the preset threshold, it means that the corresponding ship's berthing deviation is low.

[0153] It should be noted that the path deviation coefficient reflects the degree of deviation of the ship during the docking process, and the larger the value of the path deviation coefficient, the higher the corresponding degree of ship deviation.

[0154] In S3, based on the deviated ship path, it is analyzed whether the path deviation is due to the influence of the reflectivity change of the laser signal and the multipath reflection on the ranging data;

[0155] Evaluate the impact of reflectivity and environmental interference on path planning accuracy, calculate the interference index, and evaluate the degree of interference factors on path accuracy, including:

[0156] S3: Based on the deviated ship path, analyze whether the path deviation is due to the reflectivity change of the laser signal and the influence of multipath reflection on the ranging data;

[0157] Evaluate the impact of reflectivity and environmental interference on path planning accuracy, calculate the interference index, and evaluate the degree of interference factors on path accuracy, including:

[0158] By real-time monitoring of the intensity changes of the reflected signal obtained by the laser ranging equipment, the changes in the laser signal during reflection are analyzed;

[0159] When the laser signal reflects off multiple surfaces and returns to the ranging device, multiple reflection paths are generated, and these paths have different lengths, resulting in the received signal containing multiple reflection sources;

[0160] Analyze multipath reflections, compare the time delay difference between multipath reflections and direct path reflections, and identify ranging errors caused by multipath effects;

[0161] Based on the analysis results of reflectivity changes and multipath reflections, the interference index is calculated, and the specific impact of reflectivity and environmental interference on the accuracy of path planning is evaluated according to the calculated interference index;

[0162] The process of obtaining the interference index is as follows:

[0163] The interference index is calculated by particle filtering, including:

[0164] Initialize the particle swarm, which consists of particles, each particle represents an interference state, and the particle set , where each particle The state vector includes:

[0165] No. The reflectivity of each particle indicates the reflection intensity of the laser signal;

[0166] : No. The time delay of each particle represents the signal propagation delay caused by multipath reflections;

[0167] : No. The state vector of each particle contains the position and speed information of the ship;

[0168] in, represents a particle in a particle group, represents the total number of particles;

[0169] At each time step, particle prediction is performed based on the particle state transition model, and the predicted state of each particle is calculated. The calculation expression is:

[0170] ;

[0171] in, The transfer function represents the state of the particle, which predicts the state at the current moment based on the state at the previous moment;

[0172] Represents process noise

[0173] According to the real-time acquired reflection signal data, the particle weight is updated and the Weight , the calculation expression is;

[0174] ;

[0175] in, For particles At the moment The probability of measurement under Represents particles At the moment The weight of

[0176] Resample the particle swarm and regenerate the particle set ;

[0177] in, Indicates the moment of each collection;

[0178] Based on the updated particle set, the interference index is calculated, and the calculation expression is:

[0179] ;

[0180] In the formula, represents the interference index, Indicates The deviation between the reflectivity and time delay of each particle and the actual value is calculated as follows;

[0181] ;

[0182] In the formula, represents the actual measured reflectivity, represents the actual measured time delay;

[0183] According to the calculated interference index, the influence of reflectivity and environmental interference on the accuracy of path planning is evaluated;

[0184] It is determined whether the interference index is greater than or equal to a preset threshold. If so, it means that the corresponding reflectivity and environmental interference have a high degree of influence on the accuracy of path planning. If not, it means that the corresponding reflectivity and environmental interference have a low degree of influence on the accuracy of path planning.

[0185] It should be noted that the interference index reflects the degree to which the ship's reflectivity and environmental interference affect the accuracy of path planning, and the larger the value of the interference index, the higher the corresponding interference level.

[0186] In S4, based on the evaluation results, the path is corrected, the path planning model is updated, the optimal path between the ship and the berth is recalculated, the heading, speed and attitude are adjusted to ensure that the new path is accurate and avoids environmental interference, including:

[0187] According to the specific influence of reflectivity and environmental interference on the accuracy of path planning, combined with the interference coefficient and the heading and speed of the ship, the correction coefficient is comprehensively calculated for path correction and update;

[0188] The process of obtaining the correction coefficient is as follows:

[0189] The Bayesian network is used to calculate the correction factor, including:

[0190] Input variables include: speed, heading and disturbance coefficient;

[0191] Target variable: correction factor;

[0192] Set the dependency between input variables and target variables as conditional probabilities;

[0193] Constructing a conditional probability table, including: defining a prior distribution of a prior probability correction coefficient, which represents the distribution of the correction coefficient without any observed data;

[0194] Define conditional probability, given the speed and heading information, and predict the impact of reflectivity and environmental interference on the correction factor;

[0195] The posterior probability distribution of the correction coefficient is calculated using Bayes' theorem, and the calculation expression is:

[0196] ;

[0197] in, represents the prior probability of the correction coefficient, represents the conditional probability of ship speed under a given correction factor, represents the conditional probability of the heading angle under a given correction factor, represents the conditional probability of the interference coefficient under a given correction factor;

[0198] The posterior probability of the correction coefficient is calculated by the Bayesian inference algorithm. According to the posterior probability of the correction coefficient, the correction coefficient is calculated. The calculation expression is:

[0199] ;

[0200] in, represents the calculated correction factor, Indicates the current speed of the ship. Indicates the current heading of the ship. Indicates the current interference coefficient of the ship.

[0201] In S5, the dynamic behavior of the ship is adjusted in real time according to the corrected path and changes in environmental factors, and the relative position and posture between the ship and the berth are optimized. By continuously updating the path, the ship can be ensured to dock safely and accurately at the berth. Specifically, it includes:

[0202] The calculated correction coefficient is applied to path correction, and the corrected path calculation expression is:

[0203] ;

[0204] In the formula, represents the corrected path, Represents the original path, represents the increment of path correction;

[0205] Corrections are made to all vessels with deviations.

[0206] It should be noted that during the path correction and update process, the system first monitors the changes in environmental factors in real time, such as wave amplitude, light changes and obstacle dynamics, and dynamically adjusts the ship's heading, speed and attitude according to these changes; using the corrected path model, the ship's motion state will be adjusted to the optimal level to ensure that potential interference factors or obstacles are avoided during the berthing process; especially in a dynamic environment, the path will be continuously optimized, and the system will make forward-looking adjustments to the path by predicting and analyzing future environmental changes to avoid affecting the berthing accuracy due to unforeseen factors;

[0207] The heading angle and speed will be finely adjusted according to the relative position between the ship and the berth to ensure that the ship can sail to the berth smoothly and accurately. Through continuous path updates and corrections, the ship's posture will be optimized to ensure that the ship can maintain a precise docking angle and position when approaching the berth, thereby ensuring that the ship can complete the berthing task safely and accurately.

[0208] See also Figure 2 As shown, a laser ranging-based ship automatic assisted berthing system comprises:

[0209] A data acquisition module, wherein the data acquisition module uses a laser rangefinder, an ultrasonic sensor, and a visual camera to synchronously collect environmental data and location information between the vessel and the berth;

[0210] A path deviation assessment module, which generates a berthing path using a berthing model and a dynamic model based on the collected environmental data and the current position of the vessel, assesses the accuracy of the generated berthing path, and predicts the potential deviation range of the path;

[0211] An interference assessment module, which analyzes, based on the deviated ship path, whether the path deviation is due to the influence of reflectivity change of the laser signal and multipath reflection on the ranging data, and assesses the influence of reflectivity and environmental interference on the accuracy of path planning;

[0212] A path correction and vessel adjustment module, which corrects the path according to the evaluation results, updates the path planning model, recalculates the optimal path between the vessel and the berth, adjusts the course and speed of the vessel, ensures that the new path is accurate, and avoids environmental interference;

[0213] A path updating module adjusts the dynamic behavior of the vessel in real time according to the corrected path and changes in environmental factors, optimizes the relative position and posture between the vessel and the berth, and ensures that the vessel can dock with the berth safely and accurately by updating the path.

[0214] The working principle of the present invention is to ensure that the ship can dock safely and accurately at the berth through multi-sensor data fusion, path planning, correction and real-time adjustment. The present invention first uses laser ranging equipment, ultrasonic sensors and visual cameras to synchronously collect environmental data and location information between the ship and the berth, including the distance information of the berth edge and dock obstacles and the current position, heading angle and speed state of the ship. Then, the berth model and the dynamic model are combined to generate a preliminary berthing path, and the path accuracy is evaluated by the path deviation coefficient and Kalman filter prediction. Subsequently, based on the analysis of laser reflectivity and multi-path reflection, the interference index is calculated to evaluate the impact of environmental interference on the path planning accuracy. According to the evaluation results, the path is adjusted, the heading, speed and attitude are corrected, and the correction coefficient is further calculated through the Bayesian network to update the path model to ensure that the ship can accurately avoid interference factors and dock safely and accurately. The present invention optimizes the relative position between the ship and the berth through real-time path correction and dynamic behavior adjustment, and finally achieves accurate docking of the ship.

[0215] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0216] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0217] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0218] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0219] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for automatic assisted berthing of a ship based on laser ranging, characterized in that: The following steps are involved: S1: Use laser ranging equipment, ultrasonic sensors and visual cameras to synchronously collect environmental data and location information between the ship and the berth; The environmental data includes the berth edge position, the dock obstacle position and relative distance information, and the position information includes the current position, heading angle and speed status of the vessel; S2: Generate a berthing path using the berthing model and the dynamic model based on the collected environmental data and the current position of the vessel, evaluate the accuracy of the generated berthing path, and predict the potential deviation range of the path; S3: Based on the deviated ship path, analyze whether the path deviation is due to the reflectivity change of the laser signal and the influence of multipath reflection on the ranging data, and evaluate the influence of reflectivity and environmental interference on the accuracy of path planning; S4: Based on the evaluation results, the path is corrected, the path planning model is updated, the optimal path between the ship and the berth is recalculated, and the ship's heading and speed are adjusted to ensure that the new path is accurate and avoids environmental interference; S5: According to the corrected path and changes in environmental factors, the dynamic behavior of the ship is adjusted in real time to optimize the relative position and posture between the ship and the berth. By updating the path, it is ensured that the ship can dock safely and accurately at the berth.

2. The method for automatic assisted berthing of a ship based on laser ranging according to claim 1, characterized in that: The accuracy assessment of the generated berthing path and the prediction of the potential deviation range of the path specifically include: The collected environmental data is integrated with the current position, heading angle and speed state of the ship, and the berth model including the berth edge and berth space shape and the ship's dynamic model is combined to calculate the optimal path from the current position of the ship to the berth; Based on the berth model and the dynamic model, combined with the current navigation status of the ship including speed and direction, a preliminary berthing path is generated, which includes each position point, heading and speed information of the ship; By comparing the generated path with the actual trajectory of the ship, the path deviation coefficient is calculated; The path deviation coefficient calculates the path deviation by analyzing the distance error between each point on the path and the actual ship position, and evaluates the accuracy of the ship during the berthing process; The deviation of the vessel's berthing path is evaluated by calculating the path deviation coefficient.

3. The method for automatic assisted berthing of a ship based on laser ranging according to claim 2, characterized in that: The process of obtaining the path deviation coefficient is as follows: Get the ship's heading angle, speed and two-dimensional coordinates, and construct the state vector ; in, ; In the formula, and Represents the two-dimensional coordinates of the ship at its current position, Indicates the heading angle of the ship. Indicates the speed of the ship, Represents each time point of data collection; According to the dynamic model of the ship, the state transfer equation is established to describe the motion state of the ship. The calculation expression is: ； In the formula, represents the state transfer matrix, represents the control input matrix, represents the control input, represents process noise; Based on the environmental sensor data, a measurement model is established, and the calculation expression is: ； In the formula, Indicates the actual position of the vessel, represents the measurement matrix, represents the observation noise; Perform Kalman filter prediction and update to obtain the estimated state of the ship ; The steps of the prediction are: ； ； The updating steps are: ； ； ； in, represents the Kalman gain, represents the observation noise covariance matrix, represents the process noise covariance matrix, represents the estimation error covariance matrix, represents the prediction error covariance matrix; At each time step, the Kalman filter will give the predicted value of the current position coordinates of the ship, obtain the actual observed value of the ship's position coordinates, and calculate the deviation value between the predicted position and the actual position. The calculation expression is; ； In the formula, Indicates The deviation value at each time point, and Represents the predicted value of the current position coordinates, and The coordinates of the ship's position representing the actual observations; The deviation measure of the entire berthing path is obtained by accumulating the deviation value at each time point, which is recorded as the path deviation coefficient. The calculation expression is: ； In the formula, represents the path deviation coefficient, Indicates the total number of time points.

4. The method for automatic assisted berthing of a ship based on laser ranging according to claim 1, characterized in that: The evaluation of the influence of reflectivity and environmental interference on the accuracy of path planning specifically includes: By real-time monitoring of the intensity changes of the reflected signal obtained by the laser ranging equipment, the changes in the laser signal during reflection are analyzed; When the laser signal reflects off multiple surfaces and returns to the ranging device, multiple reflection paths are generated, and these paths have different lengths, resulting in the received signal containing multiple reflection sources; Analyze multipath reflections, compare the time delay difference between multipath reflections and direct path reflections, and identify ranging errors caused by multipath effects; Based on the analysis results of reflectivity changes and multipath reflections, the interference index is calculated. According to the calculated interference index, the specific impact of reflectivity and environmental interference on the accuracy of path planning is evaluated.

5. The method for automatic assisted berthing of a ship based on laser ranging according to claim 4, characterized in that: The process of obtaining the interference index is as follows: The interference index is calculated by particle filtering, including: Initialize the particle swarm, which consists of particles, each particle represents an interference state, and the particle set , where each particle The state vector includes: : No. The reflectivity of each particle indicates the reflection intensity of the laser signal; : No. The time delay of each particle represents the signal propagation delay caused by multipath reflections; : No. The state vector of each particle contains the position and speed information of the ship; in, represents a particle in a particle group, represents the total number of particles; At each time step, particle prediction is performed based on the particle state transition model, and the predicted state of each particle is calculated. The calculation expression is: ； in, The transfer function represents the state of the particle, which predicts the state at the current moment based on the state at the previous moment; represents process noise; According to the real-time acquired reflection signal data, the particle weight is updated and the Weight , the calculation expression is; ； in, For particles At the moment The probability of measurement under Represents particles At the moment The weight of Resample the particle swarm and regenerate the particle set ; in, Indicates the moment of each collection; Based on the updated particle set, the interference index is calculated, and the calculation expression is: ； In the formula, represents the interference index, Indicates The deviation between the reflectivity and time delay of each particle and the actual value is calculated as follows; ； In the formula, represents the actual measured reflectivity, represents the actual measured time delay; Based on the calculated interference index, the influence of reflectivity and environmental interference on the accuracy of path planning is evaluated.

6. The method for automatic assisted berthing of a ship based on laser ranging according to claim 1, characterized in that: The path correction is performed according to the evaluation result, specifically including: According to the specific impact of reflectivity and environmental interference on the accuracy of path planning, combined with the interference coefficient and the heading and speed of the ship, the correction coefficient is comprehensively calculated for path correction and update.

7. The method for automatic assisted berthing of a ship based on laser ranging according to claim 6, characterized in that: The process of obtaining the correction coefficient is as follows: The Bayesian network is used to calculate the correction factor, including: Input variables include: speed, heading and disturbance coefficient; Target variable: correction factor; Set the dependency between input variables and target variables as conditional probabilities; Constructing a conditional probability table, including: defining a prior distribution of a prior probability correction coefficient, which represents the distribution of the correction coefficient without any observed data; Define conditional probability, given the speed and heading information, and predict the impact of reflectivity and environmental interference on the correction factor; The posterior probability distribution of the correction coefficient is calculated using Bayes' theorem, and the calculation expression is: ； in, represents the prior probability of the correction coefficient, represents the conditional probability of ship speed under a given correction factor, represents the conditional probability of the heading angle under a given correction factor, represents the conditional probability of the interference coefficient under a given correction factor; The posterior probability of the correction coefficient is calculated by the Bayesian inference algorithm. According to the posterior probability of the correction coefficient, the correction coefficient is calculated. The calculation expression is: ； in, represents the calculated correction factor, Indicates the current speed of the ship. Indicates the current heading of the ship. Indicates the current interference coefficient of the ship; The calculated correction coefficient is applied to the path correction, and the calculation expression of the corrected path is: ； In the formula, represents the corrected path, Represents the original path, Indicates the increment of the path correction.

8. An automatic assisted berthing system for ships based on laser ranging, characterized in that: A method for automatically assisting a ship in berthing based on laser ranging as claimed in any one of claims 1 to 7, comprising: A data acquisition module, wherein the data acquisition module uses a laser rangefinder, an ultrasonic sensor, and a visual camera to synchronously collect environmental data and location information between the vessel and the berth; A path deviation assessment module, which generates a berthing path using a berthing model and a dynamic model based on the collected environmental data and the current position of the vessel, assesses the accuracy of the generated berthing path, and predicts the potential deviation range of the path; An interference assessment module, which analyzes, based on the deviated ship path, whether the path deviation is due to the influence of reflectivity change of the laser signal and multipath reflection on the ranging data, and assesses the influence of reflectivity and environmental interference on the accuracy of path planning; A path correction and vessel adjustment module, which corrects the path according to the evaluation results, updates the path planning model, recalculates the optimal path between the vessel and the berth, adjusts the course and speed of the vessel, ensures that the new path is accurate, and avoids environmental interference; A path updating module adjusts the dynamic behavior of the vessel in real time according to the corrected path and changes in environmental factors, optimizes the relative position and posture between the vessel and the berth, and ensures that the vessel can dock with the berth safely and accurately by updating the path.

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