Tagged Point-Cloud Sensor for Collaborative Robot Safety Monitoring
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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 tag detection to exclude mobile body data, allowing safe monitoring and 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 is reduced due to unnecessary stops when mobile devices approach
Solution Approach 1:
The detection system segments objects into different categories (workers vs. mobile devices) using tag detection. Workers are identified by absence of tags while mobile devices are identified by presence of tags, allowing differentiated safety responses that maintain productivity while ensuring worker safety.
Solution Approach 2:
The system applies different safety monitoring qualities to different object types. Mobile devices with tags receive a different level of monitoring (excluded from safety stop triggers) compared to workers without tags, allowing localized quality differentiation in safety response based on object identity.
2Reliability
If the robot continuously monitors all approaching objects, then safety is maintained, but productivity decreases due to frequent unnecessary decelerations
Solution Approach 1:
The system extracts and excludes mobile device data from safety monitoring by detecting tags on mobile devices. This extraction allows the safety monitoring system to focus only on workers, maintaining comprehensive safety monitoring for vulnerable persons while excluding non-vulnerable mobile devices that would otherwise trigger unnecessary stops.
3Productivity
If the sensor distinguishes between workers and mobile devices using tag detection, then productivity is enhanced by reducing unnecessary stops, but device complexity increases
Solution Approach 1:
The tag detection system serves multiple functions: it identifies mobile devices for exclusion from safety stops, provides object classification, and enables differentiated monitoring strategies. This multi-functionality allows the added complexity to serve multiple productivity-enhancing purposes rather than a single function.
Data Source
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.