Mobile Machine Path Planning With Adaptive Tunnel Safety Margins
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Solution Overview
Problem
Existing path planning methods for mobile machines often result in suboptimal movement due to fixed or inflexible safety margins, which can either prevent passage through sufficient spaces or compromise safety by allowing the machine to move too close to obstacles.
Innovation Solution
A method and system for a mobile machine to generate a point cloud of its surroundings, identify tunnel candidates, select a target tunnel based on a planned path, and set a dynamic safety margin based on the width of the tunnel to ensure safe and efficient movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed safety margin is used in path planning, then the mobile machine maintains consistent safety distance from obstacles, but it cannot pass through sufficient spaces and movement efficiency decreases
Solution Approach 1:
The patent applies dynamics by transforming the fixed safety margin into a dynamic, adjustable parameter. The safety margin is dynamically adjusted based on the width of detected tunnel spaces and the width of the mobile machine. When a tunnel space is detected, the safety margin is set to the difference between the tunnel width and machine width, allowing the machine to safely pass through narrow spaces. This dynamic adjustment resolves the contradiction by enabling both safety maintenance and efficient movement through varying environments.
Solution Approach 2:
The patent changes the parameter of safety margin from a fixed value to a variable that adapts to environmental conditions. By detecting tunnel candidates and calculating the difference between tunnel width and machine width, the system modifies the safety margin parameter in real-time. This parameter change allows the machine to use smaller safety margins in narrow passages (improving efficiency) while maintaining adequate safety distances in open areas (preserving reliability).
2Reliability
If a large safety margin is used, then collision avoidance is improved, but the mobile machine cannot move through narrow spaces
Solution Approach 1:
The patent applies local quality by making the safety margin spatially adaptive rather than uniformly applied. The safety margin is locally adjusted based on the specific tunnel space detected in each direction. When tunnel candidates are detected, the safety margin is set according to the local space width, allowing the machine to navigate narrow passages while maintaining collision avoidance through the calculated safety buffer. This local adaptation resolves the contradiction between collision avoidance and passage capability.
Solution Approach 2:
The system changes the safety margin parameter based on detected environmental parameters (tunnel width and machine width). By calculating the difference between these parameters, the system dynamically adjusts the safety margin to enable passage through narrow spaces while preserving collision avoidance capabilities. This parameter adaptation allows the machine to access previously unreachable narrow areas.
3Productivity
If a small safety margin is used, then movement efficiency through narrow spaces improves, but safety is compromised
Solution Approach 1:
The patent makes the safety margin dynamic by continuously detecting tunnel candidates and adjusting the margin based on the detected space width. When narrow tunnel spaces are detected, the safety margin is reduced to the minimum necessary value (difference between tunnel and machine width), improving movement efficiency. When larger spaces are detected or no tunnels are present, the safety margin increases, maintaining safety. This dynamic adjustment resolves the contradiction between efficiency and safety.
Solution Approach 2:
The system implements feedback by continuously monitoring the environment for tunnel candidates and using this information to adjust the safety margin. The detection results feed back into the path planning system, which modifies the safety margin parameter accordingly. This feedback mechanism ensures that the safety margin is always appropriate for the current environmental context, maintaining both efficiency and safety.
Data Source
AI summary
A mobile machine for adjusting a safety margin and a moving method thereof are provided. The moving method includes generating a point cloud representing surrounding objects by sensing the surrounding objects of the mobile machine, determining tunnel candidates between the surrounding objects by using the point cloud, selecting a target tunnel from the tunnel candidates based on a planned path, setting a safety margin based on a width of the target tunnel, and moving along the planned path while performing collision avoidance based on the safety margin.