Autonomous Material Vehicles With Controlled-Zone Safety Scanning
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Solution Overview
Problem
There is a need to maintain safety in industrial controlled zones without relying solely on human discretion, especially with the introduction of self-driving material-transport vehicles that require ensuring no human entry while operating alongside machines.
Innovation Solution
The implementation of a method and system for robotic equipment to capture environmental data, compare it with known-good data, and operate in a safe mode by limiting speed or preventing movement within controlled zones, using sensors like LiDAR and cameras to determine environmental changes and prevent unsafe conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If self-driving material-transport vehicles operate in controlled zones, then productivity and automation are improved, but safety risks increase due to potential human entry
Solution Approach 1:
The system performs preliminary environmental scanning and comparison before the vehicle enters the controlled zone. By capturing images of the controlled zone beforehand and comparing them with current images, the system proactively identifies human presence or environmental changes that would prevent safe entry, thereby preventing safety incidents before they occur
Solution Approach 2:
The system continuously monitors the controlled zone by capturing environmental data and comparing it with stored baseline data. This feedback mechanism allows the vehicle to detect human presence, environmental changes, or unsafe conditions in real-time and adjust its operation accordingly, stopping or preventing entry when safety conditions are not met
2Reliability
If environmental monitoring and safety checks are implemented, then safety is improved, but device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The vehicle's existing sensors and cameras serve multiple functions: navigation, obstacle detection, and environmental monitoring for safety. By utilizing the same imaging devices for both navigation and safety monitoring, the system avoids adding dedicated complex monitoring hardware, thereby maintaining reliability while limiting the increase in device complexity
Solution Approach 2:
The system creates a digital copy or model of the controlled zone environment by storing baseline images and comparing them with current images. This copying approach allows for sophisticated environmental monitoring and safety assessment without requiring complex physical sensors, as the comparison of image data provides sufficient information to detect human presence and environmental changes
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 approach enhances safety by automatically adjusting the operation of robotic equipment to prevent entry or movement within controlled zones when unsafe conditions are detected, reducing the reliance on human intervention and ensuring a safer operational environment.
Implementation Method 1
at least one sensor comprises a LiDAR device and the captured environmental data comprise LiDAR scan data
Implementation Method 2
the at least one sensor comprises a camera and the captured environmental data comprise an image
Implementation Method 3
the at least one sensor comprises a thermal sensor and the captured environmental data comprise a temperature
Data Source
AI summary
Systems and methods for operating robotic equipment in a controlled zone are presented. The system comprises one or more self-driving material-transport vehicles having at least one sensor, non-transitory computer-readable media, and a processor in communication with the at least one sensor and media. The media stores computer instructions that configure the processor to move the vehicle towards the controlled zone in a normal mode of operation, capture environmental data associated with the controlled zone using the at least one sensor, determine environmental-change data based on comparing the captured environmental data with known-good environmental data, and operating the vehicle in a safe mode of operation based on the environmental-change data.