Inland River LiDAR Navigation with Fast Point Cloud Obstacle Detection
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Solution Overview
Problem
Autonomous unmanned vessels face challenges in real-time path planning and obstacle avoidance on inland rivers due to changing environmental conditions, such as shifting water obstacles and vessel location changes, requiring rapid and continuous processing of sensor data.
Innovation Solution
An inland river Lidar navigation system comprising a receiver, memory, processor, and display that integrates point cloud data from sensors, discards irrelevant points, and uses mathematical morphology and Kd-tree algorithms to compute and display obstacle markers on a map in real time, enhancing processing speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all point cloud data from sensors is processed in detail, then measurement precision is improved, but processing time increases and real-time capability deteriorates
Solution Approach 1:
The patent extracts only the essential and relevant point cloud data for obstacle detection while discarding irrelevant data. The processor identifies and processes only those points that contribute to obstacle detection, separating useful information from unnecessary data to achieve real-time processing without sacrificing detection precision
Solution Approach 2:
The patent applies different processing quality levels to different regions of the point cloud data. Areas with potential obstacles receive detailed processing while other regions receive simplified processing, optimizing the balance between detection precision and processing speed by allocating computational resources locally based on need
2Reliability
If comprehensive sensor data processing is performed to ensure accurate obstacle detection, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the navigation system into distinct functional modules: point cloud acquisition, data filtering, obstacle detection, and path planning. Each module performs a specific function with optimized complexity, allowing the system to achieve high reliability through modular design while keeping individual component complexity manageable
Solution Approach 2:
The patent performs preliminary filtering and preprocessing of point cloud data before main obstacle detection. By pre-processing the data to remove obvious noise and organize relevant information in advance, the system reduces the complexity of subsequent processing steps while maintaining detection reliability
3Productivity
If real-time processing of all sensor data is performed, then productivity is improved, but energy consumption increases
Solution Approach 1:
The patent applies partial processing by focusing computational effort only on relevant portions of the sensor data that are likely to contain obstacle information. Rather than processing all data points equally, the system selectively processes only the necessary subset, achieving real-time path updates with reduced energy consumption
Data Source
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AI summary
This invention discloses an inland river Lidar navigation system for vessels, comprising a receiver, a memory, a processor and a display. The processor coupled to the receiver and the memory, and the display coupled to the processor. Overall, the inland river navigation Lidar system based on Lidar is able to make use of the preset map data identification uncalculatable points of a point cloud of the predetermined procedure, thereby removing of the alignment step in traditional method can be omitted. Therefore, the processing speed can be improved.