Tag-Based Sensor Filtering for Collaborative Robot Safety Zones
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Solution Overview
Problem
Existing systems decelerate or stop robots when any object approaches, including mobile devices, leading to reduced productivity at production sites where robots and workers collaborate.
Innovation Solution
A sensor system that generates distance and luminance images, creates point cloud data, and uses tags to differentiate between workers and mobile bodies, allowing safe exclusion of mobile body data from monitoring, thus avoiding unnecessary robot deceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot is decelerated or stopped when any object approaches the hazard, then worker safety is improved, but productivity deteriorates due to unnecessary stops when mobile devices approach
Solution Approach 1:
The system segments the detected objects into different categories (workers vs. mobile devices) using tag detection and point cloud analysis. By dividing the monitoring approach into distinct identification and classification stages, the system can apply different response rules to different object types, allowing mobile devices to pass through without triggering robot stops while maintaining safety protocols for workers.
Solution Approach 2:
The system introduces tags as intermediary markers attached to mobile devices. These tags serve as mediators that enable the sensor to distinguish between workers and mobile devices without direct physical interaction. The tag detection mechanism acts as an intermediate layer between the robot's safety monitoring and the mobile devices, allowing the system to recognize and exclude mobile devices from triggering safety stop conditions.
2Reliability
If the sensor monitors all objects in the predetermined region, then safety monitoring is improved, but device complexity increases due to processing all point cloud data including mobile devices
Solution Approach 1:
The system extracts and removes point cloud data corresponding to mobile devices from the overall monitoring data set. By separating mobile device data from worker data through tag-based identification and spatial analysis, the system reduces the complexity of safety monitoring processing while maintaining comprehensive safety coverage for workers. The extracted mobile device data is excluded from triggering safety responses.
Solution Approach 2:
The system dynamically adjusts the monitoring scope based on object identification. When a mobile device is detected via tag, the system dynamically modifies which point cloud data is processed for safety monitoring purposes. This dynamic adjustment allows the system to maintain high safety monitoring capability for workers while reducing processing complexity by excluding mobile device data from the safety decision-making pipeline.
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
Enhances productivity by preventing unnecessary robot stops when mobile devices enter the protected area, ensuring safety while maintaining operational efficiency.
Implementation Method 1
an image generation unit configured to generate a distance image and a luminance image of a predetermined region
Data Source
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AI summary
To enhance productivity at a production site where a robot and a worker work together. A sensor includes an image generation unit configured to generate a distance image and a luminance image of a predetermined region, a first point cloud data creation unit configured to create, on the basis of the distance image, first point cloud data that is point cloud data of the predetermined region, a mask data creation unit configured to create, when a tag is detected from the luminance image, mask data for masking a predetermined range in the predetermined region on the basis of an analysis result obtained by analyzing the tag, and a second point cloud data creation unit configured to create second point cloud data by excluding point cloud data of a mobile body provided with the tag from the first point cloud data on the basis of the mask data.