Autonomous Transport Vehicle Vision Sensing for Precise Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing automated storage and retrieval systems rely on limited navigation and hazard detection methods, such as location beacons and narrowly focused beam sensors, which provide insufficient information for precise navigation and hazard identification, leading to inefficiencies and potential safety issues.
Innovation Solution
The implementation of a supplemental navigation and hazard sensor system, including stereo vision and imaging radar, enhances the accuracy of vehicle and payload positioning and enables opportunistic hazard detection, allowing for autonomous vehicles to collaborate with operators for precise navigation and hazard mitigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If location beacons and narrowly focused beam sensors are used for navigation and hazard detection, then the system structure remains simple, but the measurement precision and reliability of navigation and hazard identification deteriorate
Solution Approach 1:
The patent combines multiple sensor types (stereo vision cameras, imaging radar, and existing physical characteristic sensors) into an integrated supplemental navigation and hazard sensor system. This merging allows the system to achieve high measurement precision for vehicle and payload positioning while sharing processing infrastructure and data fusion mechanisms across sensor types.
Solution Approach 2:
The supplemental sensor system serves multiple functions simultaneously: navigation, hazard detection, and payload positioning. The stereo vision and imaging radar systems are designed to perform both navigation tasks and hazard identification, eliminating the need for separate dedicated sensor systems for each function.
2Reliability
If location beacons and narrowly focused beam sensors are used, then the device complexity remains low, but the reliability of hazard detection and navigation deteriorates
Solution Approach 1:
The patent merges hazard detection capabilities into the existing navigation sensor system by adding stereo vision and imaging radar. This integration allows the same sensor infrastructure to serve both navigation and hazard detection functions, improving reliability without proportionally increasing system complexity.
Solution Approach 2:
The system continuously processes sensor data to provide real-time feedback on vehicle position, payload position, and potential hazards. This feedback mechanism enables dynamic adjustment of navigation paths and hazard response strategies, significantly improving detection reliability through continuous monitoring and verification.
3Productivity
If limited sensor information is used, then the ease of operation is maintained, but the productivity of storage and retrieval operations deteriorates due to transport errors
Solution Approach 1:
The autonomous transport vehicle performs self-positioning and self-monitoring using the supplemental navigation and hazard sensor system. The vehicle independently processes sensor data to determine its own position, detect hazards, and adjust its navigation, eliminating the need for manual intervention and improving operational efficiency.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is processed to provide real-time information about vehicle and payload position. This feedback enables automatic correction of positioning errors and及时调整 of operations, significantly improving productivity while maintaining ease of operation through automated 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
This system reduces case unit transport errors and increases the efficiency of storage and retrieval operations by providing precise vehicle and payload localization and enabling real-time hazard detection and mitigation, thereby improving overall system performance.
Implementation Method 1
stereo vision that is focused on at least a payload bed of the autonomous transport vehicle so that a controller or human operator of the storage and retrieval system monitors case unit transport
Implementation Method 2
imaging radar systems that independently measure a size and a center point of front faces of case units disposed in storage spaces on storage shelves
Data Source
AI summary
An autonomous guided vehicle includes a frame, a drive section, a payload handler, a sensor system, and a supplemental sensor system. The sensor system has electro-magnetic sensors, each responsive to interaction or interface of a sensor emitted or generated electro-magnetic beam or field with a physical characteristic, the electro-magnetic beam or field being disturbed by interaction or interface with the physical characteristic, and which disturbance is detected by and effects sensing of the physical characteristic. The sensor system generates sensor data embodying at least one of a vehicle navigation pose or location information and payload pose or location information. The supplemental sensor system supplements the sensor system, and is, at least in part, a vision system with cameras disposed to capture image data informing the at least one of a vehicle navigation pose or location and payload pose or location supplement to the information of the sensor system.