Forklift Aisle Guidance Using Onboard Sensor Mapping
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Solution Overview
Problem
Conventional guidance systems for material handling vehicles require external infrastructure, which is costly and cumbersome, and impose training requirements on operators, limiting their flexibility and efficiency.
Innovation Solution
A sensor and processor-based system that measures distances to external objects, transforms the data into a vehicle coordinate system, performs pattern recognition to identify aisle features, and provides guidance instructions without external infrastructure, allowing for autonomous or semi-autonomous navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If external infrastructure (wire guidance system) is used to guide material handling vehicles, then guidance accuracy and reliability are improved, but system cost and complexity increase
Solution Approach 1:
The patent extracts the guidance functionality from external infrastructure and relocates it to the vehicle itself through onboard sensors (LIDAR, cameras, ultrasonic sensors) and processing units. This eliminates the need for wires, reflectors, and other external infrastructure while maintaining guidance capability through environmental feature detection and mapping.
Solution Approach 2:
The material handling vehicle performs its own guidance function using onboard sensors to detect, map, and navigate using environmental features. The vehicle independently creates and updates maps of its operating environment, identifies navigation paths, and adjusts its position without requiring external guidance infrastructure, thereby achieving self-service guidance.
2Adaptability or versatility
If external infrastructure is installed to enable vehicle guidance, then guidance functionality is achieved, but implementation cost and installation effort increase
Solution Approach 1:
The onboard sensor system serves multiple functions: it detects environmental features for guidance, creates and updates maps of the operating environment, identifies obstacles, and supports navigation decisions. This multi-functional approach eliminates the need for specialized external infrastructure while providing comprehensive guidance capability across various environments.
Solution Approach 2:
The system creates a digital copy or map of the physical environment using sensor data from LIDAR, cameras, and ultrasonic sensors. This virtual representation of the operating environment allows the vehicle to navigate by comparing its actual position against the stored map, eliminating the need for physical guidance infrastructure like wires or reflectors.
3Measurement precision
If conventional guidance systems with external infrastructure are used, then vehicle alignment is achieved, but operator training requirements increase
Solution Approach 1:
The patent replaces mechanical/wire-based guidance systems with an optical and electronic sensing system. LIDAR, cameras, and ultrasonic sensors detect environmental features and provide precise position measurement through electromagnetic and acoustic fields, eliminating the need for physical wire infrastructure and reducing operator training requirements.
Solution Approach 2:
The system continuously monitors the vehicle's position relative to the mapped environment using onboard sensors and provides real-time feedback for position correction. The processing unit compares current sensor data against the stored environmental map, calculates position deviations, and generates correction commands to maintain accurate alignment, enabling autonomous operation with minimal operator intervention.
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 efficient and cost-effective guidance of material handling vehicles within an operating environment, reducing the need for external infrastructure and operator training, while accommodating aisle variability and obstacles.
Implementation Method 1
a sensor configured to measure a distance to an external object within a field of view of the sensor
Implementation Method 2
a sensor configured to measure a distance to an external object
Data Source
AI summary
Guidance systems and methods for a material handling vehicle are provided. A guidance system can include a sensor and a processor unit. The sensor can be configured to measure a distance to an external object within a field of view of the sensor and output distance information corresponding to the measured distance. The processor can be configured to receive the distance information from the sensor, transform the distance information from a sensor coordinate system to a material handling vehicle coordinate system, perform pattern recognition on the transformed distance information to identify an aisle feature, create an aisle model based on the identified aisle feature, and determine a guidance instruction for the material handling vehicle based on the aisle model. The aisle model can include information corresponding to the aisle feature. The guidance instruction may be configured to align the material handling vehicle within an aisle.