Autonomous 3D Laser Scanning Path Planning for Complex Structures
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Solution Overview
Problem
Existing methods for autonomous or semi-autonomous scanning exploration by UAVs struggle with complex objects such as bridges or buildings with canopies or complicated façades, often resulting in scan shadows and excessive time consumption due to battery limitations.
Innovation Solution
A computer-implemented method for autonomously exploring objects of interest using a mobile robot equipped with a computing unit and a laser scanner module, which involves defining a three-dimensional exploration map, partitioning it into blocks, and updating the map while the robot travels along an exploration path, determining unexplored blocks, and assigning scores for optimal path planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods for autonomous scanning exploration by UAVs are used, then simple objects can be scanned, but complex objects result in scan shadows and excessive time consumption
Solution Approach 1:
The exploration space is divided into multiple three-dimensional exploration blocks, allowing the UAV to systematically scan complex objects by processing each block individually. This segmentation enables complete coverage of complex surfaces including bridges and buildings with canopies or complicated façades without creating scan shadows, while maintaining efficient scanning through structured block-by-block exploration.
2Productivity
If existing methods for autonomous scanning exploration by UAVs are used, then scanning can be performed, but battery limitations restrict operational duration
Solution Approach 1:
The system performs preliminary actions by defining the exploration space and partitioning it into exploration blocks before the UAV begins scanning. The computing unit calculates optimal exploration paths in advance, allowing the UAV to efficiently navigate and scan complex objects without unnecessary movements or delays, thereby maximizing scanning productivity within battery constraints.
Solution Approach 2:
The computing unit continuously updates the exploration map based on scan data received from the laser scanner module during UAV movement. This feedback mechanism allows real-time optimization of the exploration path, enabling the system to adapt to discovered object geometries and adjust scanning strategies to maintain high efficiency while conserving battery power.
3Extent of automation
If fully autonomous exploration is implemented, then user interaction after initial area definition is eliminated, but path optimization for complex objects becomes more challenging
Solution Approach 1:
The complex path planning problem is simplified by segmenting the exploration space into discrete three-dimensional blocks. The computing unit independently determines exploration paths for each block based on scan data, transforming a complex global optimization problem into multiple simpler local decisions. This enables fully autonomous operation while managing computational complexity through structured block-based planning.
Solution Approach 2:
The exploration path is dynamically updated by the computing unit based on real-time scan data and the evolving exploration map. As the UAV discovers new object geometries and updates the map, the path planning adapts automatically without requiring user intervention. This dynamic re-planning capability enables full autonomy while handling complex object geometries through continuous adaptation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables fully autonomous and efficient scanning of complex objects by optimizing the exploration path and reducing the time required for scanning, thereby extending the UAV's operational battery life.
Implementation Method 1
a laser scanner module for scanning surfaces of objects of interest
Implementation Method 2
generating scan data related to a point cloud while the mobile robot is travelling along an exploration path
Data Source
Figure 1~2
Figure 3~4
Figure 5a~5b
AI summary
The invention pertains to a computer-implemented method for autonomously exploring, by a mobile robot one or more objects of interest, the mobile robot comprising a computing unit and a laser scanner module for scanning surfaces of the one or more objects of interest. The method comprising defining a 3D exploration map (3), wherein the one or more objects of interest are situated in the exploration map, partitioning the exploration map into a multitude of 3D exploration blocks (30), and an autonomous exploration of the exploration map by means of the mobile robot, wherein the exploration comprises, by the laser scanner module, generating scan data related to a point cloud while the mobile robot is travelling along an exploration path (13), wherein exploring an exploration block at least comprises determining, whether the respective exploration block comprises one or more points of the point cloud, and the computing unit of the mobile robot updates the exploration map and defines the exploration path.