Raised-Floor Sensor Vehicle Path Rerouting Around Vertical Obstacles
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Solution Overview
Problem
Automated material handling systems in semiconductor fabrication facilities face challenges in adapting to changes in processing machines or tools, and manual handling is prone to human error and inefficiency.
Innovation Solution
An automated sensor vehicle equipped with a depth sensor, such as a LiDAR sensor, is used to detect vertical obstacles on a raised floorboard platform, allowing it to redirect its path and avoid inconsistencies, thereby improving the efficiency and adaptability of wafer transport within the facility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automated sensor vehicles are deployed to navigate raised floorboard platforms, then adaptability to facility layout changes is improved, but device complexity increases due to sensor integration and path planning systems
Solution Approach 1:
The patent replaces traditional mechanical guidance systems (rails, fixed paths) with optical sensing systems (cameras, LiDAR, depth sensors) and computational path planning algorithms. This substitution enables the vehicle to adapt to layout changes through software updates rather than mechanical reconfiguration, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The vehicle performs self-navigation and self-adjustment by using its own sensors to detect obstacles and calculate alternative paths in real-time. This autonomous capability eliminates the need for external guidance infrastructure, improving adaptability while the integrated nature of the system manages complexity through consolidation rather than addition.
2Reliability
If depth sensors are used to detect vertical obstacles ahead of the vehicle, then navigation reliability is improved, but measurement precision requirements increase
Solution Approach 1:
The depth sensor detects vertical obstacles at a distance ahead of the vehicle's current position, allowing the path planning system to calculate and execute avoidance maneuvers before the vehicle reaches the obstacle. This preliminary detection approach improves navigation reliability by providing advance warning, while the system tolerates moderate measurement precision through conservative path planning margins.
Solution Approach 2:
The sensor system continuously monitors the environment and provides real-time feedback to the path planning algorithm, which adjusts the vehicle's trajectory dynamically. This closed-loop control improves reliability by responding to actual conditions, while the system maintains robustness against measurement variations through adaptive rather than purely precision-dependent control.
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
The automated sensor vehicle enhances the adaptability and efficiency of wafer transport by accurately detecting and navigating around vertical obstacles, reducing the need for manual intervention and adapting to changes in the facility layout.
Implementation Method 1
A depth sensor may be configured to detect a vertical obstacle as a variation in depth along a horizontal line in front of the automated sensor vehicle
Data Source
AI summary
In an embodiment a system includes: an automated vehicle configured to traverse a first predetermined path; and a sensor system located on the automated vehicle, the sensor system configured to detect a vertical obstacle along the first predetermined path along one or two floorboards ahead of the automated vehicle, wherein the automated vehicle is configured to traverse a second predetermined path in response to detecting the vertical obstacle.