Workspace Sensor Monitoring for Dynamic Safe Zone Control
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Solution Overview
Problem
Conventional guarding systems in industrial environments are insufficiently granular to reliably monitor dynamic workspaces where humans and machinery interact, leading to potential safety hazards due to the complexity of configuring 3D sensor systems and the need for precise calculation of safe zones, which can result in conservative limitations and inefficient use of space.
Innovation Solution
A system that uses sensors distributed throughout the workspace to dynamically monitor and classify regions as occupied, unoccupied, or unknown, with real-time forecasting of human and machinery trajectories, allowing for the identification of potentially occupied spaces and the generation of safe zones without requiring discrete speed limitations, thus enabling more precise and adaptive safety protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional guarding systems (cages, light curtains, 2D LIDAR) are used to ensure human safety, then safety is improved, but workspace flexibility and human-machine interaction are severely constrained
Solution Approach 1:
The system dynamically adjusts safety zones and machine operation states based on real-time detection of human presence, proximity, and trajectory. Instead of static guarding, the safety parameters (exclusion zones, speed limitations) are continuously modified according to the detected human actions, enabling flexible human-machine collaboration while maintaining safety
Solution Approach 2:
The system changes multiple parameters simultaneously including detection sensitivity, safety zone boundaries, machine speed, and operational states based on the detected human presence and context. This allows the system to adapt safety measures to the specific situation rather than applying fixed constraints
2Productivity
If 3D sensor systems are configured to detect intrusions tightly near machinery, then workspace efficiency is improved, but system complexity and configuration difficulty increase
Solution Approach 1:
The system performs self-calibration and automatic configuration by detecting the machinery boundaries and automatically establishing appropriate safety zones. The sensor system adapts to the specific workspace layout and machinery configuration without requiring extensive manual programming, reducing configuration complexity while maintaining tight safety monitoring
3Reliability
If conservative safety zones are established to ensure high probability of detecting dangerous conditions, then safety is improved, but available workspace area is reduced
Solution Approach 1:
The system applies different safety monitoring levels and zone classifications to different regions of the workspace based on the specific hazard level and human activity patterns. Critical areas near moving parts have stricter monitoring, while other areas allow more flexible access, optimizing both safety and workspace utilization
4Reliability
If discrete speed limitations are imposed on machinery to ensure safety near humans, then safety is improved, but productivity and machine throughput are reduced
Solution Approach 1:
The system dynamically adjusts machine speed and operational parameters in real-time based on the detected human presence, proximity, and trajectory. When no humans are detected or they are in safe zones, the machine operates at full speed. When humans approach hazardous areas, speed limitations are applied only to the specific axes or functions posing risk, maintaining overall productivity while ensuring safety
Data Source
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AI summary
Systems and methods monitor a workspace for safety purposes using sensors distributed about the workspace. The sensors are registered with respect to each other, and this registration is monitored over time. Occluded space as well as occupied space is identified, and this mapping is frequently updated.