Barrier lake reservoir capacity measurement underwater robot adaptive dynamic path planning method

Abstract

The dammed lake capacity measurement underwater robot adaptive dynamic path planning method comprises the following steps: a shore-based system processes dammed lake images collected by a satellite subscription camera, obtains initial boundary longitude and latitude information of the dammed lake water area, and performs rasterization processing on the dammed lake water area map; after the underwater robot is launched, the shore-based system sends the divided dammed lake area boundary information and the starting position information to each underwater robot through a communication module; the underwater robot executes an initial area coverage path, a sensor carried by the underwater robot acquires real-time underwater robot bottom height information, a local planner adopts an adaptive dynamic form to calculate and obtain a new local path; according to the scanning width and the path length of the local planning path, combined with the average bottom height on the underwater robot motion path; the scanned area is compared with the initial area of the dammed lake to determine whether the underwater robot completes the area coverage scanning task.

Description

Technical Field

[0001] This invention relates to an adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes. Background Technology

[0002] A landslide-dammed lake is a lake formed when a mountain valley or riverbed is blocked by landslides caused by volcanic lava flows, glacial till, or earthquakes, causing the valley or riverbed to accumulate water. As research into the hazards of landslide-dammed lakes has deepened, it has been discovered that dam failures pose a significant threat to the lives and property of people downstream. Therefore, it is essential to divert water from these high-risk lakes to gradually lower water levels and prevent further flooding. Simultaneously, real-time monitoring of the reservoir's capacity and dam structure is crucial. However, the complex topography and dam structure of landslide-dammed lakes present significant technical challenges for real-time capacity monitoring.

[0003] In recent years, with the development of technologies such as intelligent control, navigation and communication, underwater detection and planning and decision-making, the application of various technologies in underwater robots has become increasingly mature. This has laid a technical foundation for underwater robots to monitor changes in the capacity of landslide-dammed lakes in real time.

[0004] Most existing underwater robots rely on experience and knowledge to obtain a preset path during path planning, which limits the robot's navigation performance. This results in the robot scanning with a fixed width in waters of different depths, increasing the repetitive coverage. Furthermore, the lack of sensor data monitoring and feedback transmission leads to poor data collection quality and accuracy, limiting the robot's autonomy and intelligence, and ultimately reducing its work efficiency. Summary of the Invention

[0005] This invention provides an adaptive dynamic path planning method for underwater robots used in measuring the capacity of landslide-dammed lakes. The method is rationally designed, dividing the working area of ​​the landslide-dammed lake based on the number of deployed underwater robots and automatically calculating the optimal deployment point. This allows for low-cost searching of the landslide-dammed lake area, reducing redundant coverage by the underwater robots. Furthermore, based on real-time sensor data acquired and transmitted by the underwater robots, an adaptive dynamic path is obtained, improving the accuracy and effectiveness of data acquisition. The obtained dynamic path effectively enhances the search efficiency and intelligence of the underwater robots, enabling real-time and accurate monitoring of the landslide-dammed lake's capacity parameters, thus solving the problems existing in the prior art.

[0006] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0007] An adaptive dynamic path planning method for an underwater robot used to measure the capacity of a landslide-dammed lake, the path planning method comprising the following steps:

[0008] S1, the shore-based system will subscribe to and process the images of the landslide dammed lake captured by satellite to obtain the initial boundary latitude and longitude information of the landslide dammed lake area, and rasterize the landslide dammed lake area map to obtain evenly distributed raster data and the initial area of ​​the landslide dammed lake. The optimal deployment point of the underwater robot is calculated based on the number of underwater robots and the number of raster data.

[0009] S2. After the underwater robot is deployed, the shore-based system sends the boundary information and starting position information of the divided landslide dam area to each underwater robot through the communication module. The global planner uses the CCPP algorithm to calculate the initial area coverage path and sends the coverage path to the path tracking module of each underwater robot.

[0010] S3, the underwater robot executes the initial area coverage path. The sensors on its own body obtain the underwater robot's bottom height information in real time. Based on the bottom height information obtained in real time by the sensors and the scanning width calculation method, an optimal scanning width is obtained and transmitted to the local planner. The local planner uses an adaptive dynamic form to calculate and obtain a new local path.

[0011] S4. Based on the scanning width and path length of the local planning path, combined with the average bottom height on the underwater robot's movement path, the storage capacity corresponding to the currently scanned area is obtained in real time, and then the storage capacity is uploaded to the shore-based system through the communication module.

[0012] S5. Compare the scanned area with the initial area of ​​the landslide dammed lake to determine whether the underwater robot has completed the area coverage scanning task. If the task is not completed, repeat steps S3 and S4. When the task is completed, the shore-based system releases the capacity information of the landslide dammed lake and causes the underwater robot to return to shore.

[0013] The underwater robot is equipped with a control center, which is connected to a navigation module, a motion module, a perception module, and a planning module. The navigation module transmits the real-time pose information of the underwater robot to the motion module and the planning module. The motion module is used to accurately track the path and ensure the quality of the sensor images acquired. The perception module is used to perceive data in real time and transmit it to the planning module. The planning module is used to perceive driving data and transmit the adaptive path to the motion module.

[0014] The planning module is an adaptive dynamic path planning module, which includes a global planner and a local planner. The adaptive dynamic path planning module is also equipped with a sweep width calculator to obtain new planned paths.

[0015] In S2, the sweep length of the underwater robot's comb-shaped trajectory is parallel to the longest boundary of the region, and the sweep width of the underwater robot's comb-shaped trajectory is determined by the depth measured by the altimeter, the sonar tilt angle, and a manually set accurate threshold.

[0016] The methods for calculating scan width include those for single-beam sonar and those for multi-beam sonar.

[0017] The single-beam sonar sweep width calculation method determines the sweep width range based on the map and the underwater robot's own size, accuracy, and mission requirements. w min , w max The initial sweep width of the underwater robot is set to... w min Starting from the second scan, the underwater robot will determine the adaptive scan width at the end of each scan. w current Combined with the current scan height function h current ( x ) and the height function of the previous scan h last ( x The maximum depth variation gradient of the landslide dammed lake in the sweeping direction was obtained.

[0018]

[0019] in, w last This is the width parameter between the two scans.

[0020] The sweep width calculation method based on multibeam sonar has an opening angle range in the sweep width direction that is related to the height. After completing each sweep, the underwater robot sets the minimum height obtained in the current sweep as... h min The opening angle of the multibeam echo sounder is γ To achieve full coverage, its adaptive scan width is...

[0021]

[0022] Based on the obtained scan width data, a new local scan path is then calculated.

[0023] The formula for calculating the storage capacity is:

[0024]

[0025] Where V represents the storage capacity of the area scanned by the underwater robot. The scan width for real-time local path planning. The average bottom elevation along the underwater robot's movement path.p k This is the initial position for the new sweep width of the underwater robot. p k+1 This indicates the end position of the current sweep width of the underwater robot.

[0026] This invention employs the aforementioned structure. By rasterizing the map of the landslide dammed lake, evenly distributed raster data and the initial area of ​​the landslide dammed lake are obtained. The optimal deployment point for the underwater robots is calculated based on the number of underwater robots and the number of raster data. The global planner uses the CCPP algorithm to calculate the initial area coverage path and sends this path to the path tracking module of each underwater robot. Based on the bottom height information obtained in real time by the sensors and the scanning width calculation method, an optimal scanning width is obtained and transmitted to the local planner. The local planner uses an adaptive dynamic approach to calculate a new local planning path. By comparing the scanned area with the initial area of ​​the landslide dammed lake, it is determined whether the underwater robot has completed the area coverage scanning task. This invention has the advantages of being fast, efficient, simple, and practical. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the process of the present invention.

[0028] Figure 2 This is a schematic diagram of the underwater robot of the present invention.

[0029] Figure 3 This is a flowchart of the adaptive dynamic path planning module of the present invention.

[0030] Figure 4 This is a schematic diagram of the structure of the multibeam sonar detection model of the present invention.

[0031] Figure 5 This is a schematic diagram illustrating the deployment of the underwater robot in the landslide dammed lake according to the present invention. Detailed Implementation

[0032] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific implementation methods and in conjunction with the accompanying drawings.

[0033] like Figure 1-5 As shown in the figure, the underwater robot for measuring the capacity of a landslide dammed lake uses an adaptive dynamic path planning method, which includes the following steps:

[0034] S1, the shore-based system will subscribe to and process the images of the landslide dammed lake captured by satellite to obtain the initial boundary latitude and longitude information of the landslide dammed lake area, and rasterize the landslide dammed lake area map to obtain evenly distributed raster data and the initial area of ​​the landslide dammed lake. The optimal deployment point of the underwater robot is calculated based on the number of underwater robots and the number of raster data.

[0035] S2. After the underwater robot is deployed, the shore-based system sends the boundary information and starting position information of the divided landslide dam area to each underwater robot through the communication module. The global planner uses the CCPP algorithm to calculate the initial area coverage path and sends the coverage path to the path tracking module of each underwater robot.

[0036] S3, the underwater robot executes the initial area coverage path. The sensors on its own body obtain the underwater robot's bottom height information in real time. Based on the bottom height information obtained in real time by the sensors and the scanning width calculation method, an optimal scanning width is obtained and transmitted to the local planner. The local planner uses an adaptive dynamic form to calculate and obtain a new local path.

[0037] S4. Based on the scanning width and path length of the local planning path, combined with the average bottom height on the underwater robot's movement path, the storage capacity corresponding to the currently scanned area is obtained in real time, and then the storage capacity is uploaded to the shore-based system through the communication module.

[0038] S5. Compare the scanned area with the initial area of ​​the landslide dammed lake to determine whether the underwater robot has completed the area coverage scanning task. If the task is not completed, repeat steps S3 and S4. When the task is completed, the shore-based system releases the capacity information of the landslide dammed lake and causes the underwater robot to return to shore.

[0039] The underwater robot is equipped with a control center, which is connected to a navigation module, a motion module, a perception module, and a planning module. The navigation module transmits the real-time pose information of the underwater robot to the motion module and the planning module. The motion module is used to accurately track the path and ensure the quality of the sensor images acquired. The perception module is used to perceive data in real time and transmit it to the planning module. The planning module is used to perceive driving data and transmit the adaptive path to the motion module.

[0040] The planning module is an adaptive dynamic path planning module, which includes a global planner and a local planner. The adaptive dynamic path planning module is also equipped with a sweep width calculator to obtain new planned paths.

[0041] In S2, the sweep length of the underwater robot's comb-shaped trajectory is parallel to the longest boundary of the region, and the sweep width of the underwater robot's comb-shaped trajectory is determined by the depth measured by the altimeter, the sonar tilt angle, and a manually set accurate threshold.

[0042] The methods for calculating scan width include those for single-beam sonar and those for multi-beam sonar.

[0043] The single-beam sonar sweep width calculation method determines the sweep width range based on the map and the underwater robot's own size, accuracy, and mission requirements. wmin , w max The initial sweep width of the underwater robot is set to... w min Starting from the second scan, the underwater robot will determine the adaptive scan width at the end of each scan. w current Combined with the current scan height function h current ( x ) and the height function of the previous scan h last ( x The maximum depth variation gradient of the landslide dammed lake in the sweeping direction was obtained.

[0044]

[0045] in, w last This is the width parameter between the two scans.

[0046] The sweep width calculation method based on multibeam sonar has an opening angle range in the sweep width direction that is related to the height. After completing each sweep, the underwater robot sets the minimum height obtained in the current sweep as... h min The opening angle of the multibeam echo sounder is γ To achieve full coverage, its adaptive scan width is...

[0047]

[0048] Based on the obtained scan width data, a new local scan path is then calculated.

[0049] The formula for calculating the storage capacity is:

[0050]

[0051] Where V represents the storage capacity of the area scanned by the underwater robot. The scan width for real-time local path planning. The average bottom elevation along the underwater robot's movement path. p k This is the initial position for the new sweep width of the underwater robot. p k+1 This indicates the end position of the current sweep width of the underwater robot.

[0052] The working principle of the adaptive dynamic path planning method for underwater robots in the landslide dammed lake capacity measurement embodiment of the present invention is as follows: the working area of ​​the landslide dammed lake is divided according to the number of deployed underwater robots, and the optimal deployment point can be automatically calculated. This enables the search of the water area of ​​the landslide dammed lake at a lower cost, reducing the redundant coverage of underwater robots. At the same time, based on the real-time sensor data acquired and transmitted by the underwater robots, the acquired sensor data is fully utilized to obtain an adaptive dynamic path, improving the accuracy and effect of underwater robot data acquisition. Based on the obtained dynamic path, the search efficiency and intelligence of the underwater robots can be effectively improved, thereby enabling real-time and accurate monitoring of the landslide dammed lake capacity parameters.

[0053] Furthermore, this application, through the traditional CCPP algorithm and the proposed two-layer path planner, can dynamically plan an optimal scanning path based on real-time adaptive bottom height, thereby effectively improving the search efficiency and intelligence of the underwater vehicle.

[0054] Due to the difficulty in accessing landslide-dammed lake areas and the lack of docks, cranes, and other deployment facilities and equipment, traditional underwater robot deployment methods are difficult to implement in these areas. Furthermore, traditional underwater robot path planning schemes fail to fully utilize the information obtained from sensors, resulting in planned paths that do not fully leverage the sensor's performance advantages or make it difficult for the underwater robot to reach its destination, significantly impacting the robot's safety. The adaptive dynamic path planning method for underwater robots used in landslide-dammed lake capacity measurement proposed in this application can effectively solve these problems.

[0055] The overall solution mainly includes the following steps: S1, the shore-based system processes images of the landslide-dammed lake acquired by satellite to obtain the initial boundary latitude and longitude information of the landslide-dammed lake area, and rasterizes the landslide-dammed lake area map to obtain evenly distributed raster data and the initial area of ​​the landslide-dammed lake. The optimal deployment point for the underwater robots is calculated based on the number of underwater robots and the number of raster data. S2, after the underwater robots are deployed, the shore-based system sends the boundary information and starting position information of the divided landslide-dammed lake area to each underwater robot via a communication module. The global planner uses the CCPP algorithm to calculate the initial area coverage path and sends this coverage path to the path tracking module of each underwater robot. S3, the underwater robots execute the initial area coverage path, and their onboard sensors acquire water... The robot's bottom-altitude information is obtained in real time by sensors. An optimal scanning width is calculated using a scanning width calculation method and transmitted to the local planner. The local planner then uses an adaptive dynamic approach to calculate a new local planning path. In step S4, based on the scanning width and path length of the local planning path, combined with the average bottom-altitude height along the robot's path, the reservoir capacity corresponding to the currently scanned area is obtained in real time. This capacity is then uploaded to the shore-based system via a communication module. In step S5, the scanned area is compared with the initial area of ​​the landslide dam to determine if the underwater robot has completed the area coverage scanning task. If the task is not completed, steps S3 and S4 are repeated. When the task is completed, the shore-based system publishes the landslide dam reservoir capacity information and initiates the underwater robot's return.

[0056] The algorithm is a traditional path planning algorithm for area coverage. It mainly calculates a reciprocating scanning path based on the known initial area range and the manually set scan width. This algorithm can efficiently achieve full coverage path planning for an area.

[0057] The shore-based system processes satellite images to obtain the initial latitude and longitude information of the landslide dammed lake area, and rasterizes the map of the landslide dammed lake area to ensure the accuracy of data processing.

[0058] The control center inside the underwater robot is connected to a navigation module, a motion module, a perception module, and a planning module. The cooperation of these multiple functional modules enables the acquisition of the reservoir capacity parameters of the landslide dammed lake based on instructions from the shore-based system.

[0059] The sweep length of the underwater robot's comb-shaped trajectory is parallel to the longest boundary of the region, and the sweep width of the underwater robot's comb-shaped trajectory is determined by the current depth of the AUV, the sonar tilt angle, and a manually set accurate threshold, thus making it more suitable for the CCPP algorithm and obtaining a more efficient region coverage path.

[0060] The methods for calculating scan width mainly include those for single-beam sonar and those for multi-beam sonar.

[0061] The scan width calculation method for single-beam sonar determines the scan width range based on the map and the size, accuracy, and mission requirements of the underwater robot itself. w min , w max The initial sweep width of the underwater robot is set to... w min Starting from the second scan, the underwater robot will determine the adaptive scan width at the end of each scan. w current Combined with the current scan height function h current ( x ) and the height function of the previous scan h last ( x The maximum depth variation gradient of the landslide dammed lake in the sweeping direction was obtained.

[0062]

[0063] in, w last This is the width parameter between the two scans.

[0064] The sweep width calculation method based on multibeam sonar has a coverage range that is related to height in the sweep width direction. After completing each sweep, the underwater robot sets the minimum height obtained in the current sweep as [the minimum height]. h min The opening angle of the multibeam echo sounder is γ To achieve full coverage, its adaptive scan width is...

[0065]

[0066] Based on the obtained scan width data, a new local scan path is then calculated.

[0067] After obtaining the above-mentioned multiple types of information data, the current storage capacity of the scanned area is obtained in real time based on the scanning width and path length of the local planning path, combined with the average bottom height on the underwater robot's movement path.

[0068] The formula for calculating the storage capacity is:

[0069]

[0070] Where V represents the storage capacity of the area scanned by the underwater robot. The scan width for real-time local path planning. The average bottom elevation along the underwater robot's movement path. p k This is the initial position for the new sweep width of the underwater robot. p k+1 This indicates the end position of the current sweep width of the underwater robot.

[0071] After the reservoir capacity data is transmitted to the shore-based system, the scanned area is compared with the initial area of ​​the landslide dammed lake to determine whether the underwater robot has completed the area coverage scanning task.

[0072] It should be noted that this application is capable of adaptive dynamic path planning, which aims to calculate an adaptive dynamic path by using real-time sensor data from the underwater robot. After processing the terrain data collected according to the path, the function of real-time monitoring of the capacity of the landslide dammed lake can be realized.

[0073] In summary, the adaptive dynamic path planning method for underwater robots used to measure the capacity of landslide dammed lakes in this embodiment of the invention divides the working area of ​​the landslide dammed lake based on the number of deployed underwater robots and can automatically calculate the optimal deployment point. This method enables the search of the landslide dammed lake area at a lower cost, reduces the redundant coverage of underwater robots, and fully utilizes the real-time sensor data acquired and transmitted by the underwater robots to obtain an adaptive dynamic path. This improves the accuracy and effectiveness of underwater robot data acquisition. Based on the obtained dynamic path, the search efficiency and intelligence of the underwater robots can be effectively improved, thereby enabling real-time and accurate monitoring of the capacity parameters of the landslide dammed lake.

[0074] The above specific embodiments should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, any alternative improvements or modifications made to the embodiments of the present invention shall fall within the scope of protection of the present invention.

[0075] Any aspects of this invention not described in detail are well-known to those skilled in the art.

Claims

1. An adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes, characterized in that, The path planning method includes the following steps: S1, the shore-based system will subscribe to and process the images of the landslide dammed lake captured by satellite to obtain the initial boundary latitude and longitude information of the landslide dammed lake area, and rasterize the landslide dammed lake area map to obtain evenly distributed raster data and the initial area of ​​the landslide dammed lake. The optimal deployment point of the underwater robot is calculated based on the number of underwater robots and the number of raster data. S2. After the underwater robot is deployed, the shore-based system sends the boundary information and starting position information of the divided landslide dam area to each underwater robot through the communication module. The global planner uses the CCPP algorithm to calculate the initial area coverage path and sends the coverage path to the path tracking module of each underwater robot. S3, the underwater robot executes the initial area coverage path. The sensors on its own body obtain the underwater robot's bottom height information in real time. Based on the bottom height information obtained in real time by the sensors and the scanning width calculation method, an optimal scanning width is obtained and transmitted to the local planner. The local planner uses an adaptive dynamic form to calculate and obtain a new local path. S4. Based on the scanning width and path length of the local planning path, combined with the average bottom height on the underwater robot's movement path, the storage capacity corresponding to the currently scanned area is obtained in real time, and then the storage capacity is uploaded to the shore-based system through the communication module. S5. Compare the scanned area with the initial area of ​​the landslide dammed lake to determine whether the underwater robot has completed the area coverage scanning task. If the task is not completed, repeat steps S3 and S4. When the task is completed, the shore-based system releases the capacity information of the landslide dammed lake and causes the underwater robot to return to shore.

2. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 1, characterized in that: The underwater robot is equipped with a control center, which is connected to a navigation module, a motion module, a perception module, and a planning module. The navigation module transmits the real-time pose information of the underwater robot to the motion module and the planning module. The motion module is used to accurately track the path and ensure the quality of the sensor images acquired. The perception module is used to perceive data in real time and transmit it to the planning module. The planning module is used to perceive driving data and transmit the adaptive path to the motion module.

3. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 2, characterized in that: The planning module is an adaptive dynamic path planning module, which includes a global planner and a local planner. The adaptive dynamic path planning module is also equipped with a sweep width calculator to obtain new planned paths.

4. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 1, characterized in that: In S2, the sweep length of the underwater robot's comb-shaped trajectory is parallel to the longest boundary of the region, and the sweep width of the underwater robot's comb-shaped trajectory is determined by the depth measured by the altimeter, the sonar tilt angle, and a manually set accurate threshold.

5. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 1, characterized in that: The methods for calculating scan width include those for single-beam sonar and those for multi-beam sonar.

6. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 5, characterized in that: The single-beam sonar sweep width calculation method determines the sweep width range based on the map and the underwater robot's own size, accuracy, and mission requirements. min ,w max The initial sweep width of the underwater robot is set to w. min Starting from the second scan, the underwater robot will determine the adaptive scan width w at the end of each scan. current Combined with the current scan height function h current (x) and the height function h of the previous scan last (x) yields the maximum depth variation gradient of the landslide dammed lake along the sweep width direction. ； Among them, w last This is the width parameter between the two scans.

7. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 5, characterized in that: The sweep width calculation method based on multibeam sonar has an opening angle range in the sweep width direction that is related to the height. After completing each sweep, the underwater robot sets the minimum height obtained by the current sweep to h. min If the opening angle of the multibeam echo sounder is γ, and it aims to achieve full coverage, then its adaptive scan width is... ； Based on the obtained scan width data, a new local scan path is then calculated.

8. The adaptive dynamic path planning method for underwater robots used for measuring the capacity of landslide-dammed lakes according to claim 1, characterized in that, The formula for calculating the storage capacity is: ； Where V represents the storage capacity of the area scanned by the underwater robot. The scan width for real-time local path planning. p represents the average height to the bottom along the underwater robot's path. i p is the initial position for the new sweep width of the underwater robot. i+1 This indicates the end position of the current sweep width of the underwater robot.

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