Interactive Safety Signaling for Dynamic Human-Robot Workspaces
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Solution Overview
Problem
Industrial machinery poses hazards to humans, and existing safeguarding systems either restrict interaction or are difficult for workers to understand, leading to productivity issues and unexpected machinery stops.
Innovation Solution
A system that uses sensors and computational modeling to dynamically identify safe and unsafe zones in a 3D workspace by generating a 3D spatial representation, including safety protocols and perceptible signals such as colored illumination or audible cues, to indicate safe distances and potential hazards in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional guarding approaches (cages) are used to separate humans and machines, then safety is improved, but interaction between human and machine is prevented and workspace is severely constrained
Solution Approach 1:
The workspace is segmented into multiple safety zones (first safety zone, second safety zone, third safety zone) with different safety levels, allowing different types of human-machine interaction in different regions. This enables workers to interact with machinery in designated safe areas while maintaining overall safety through spatial segmentation.
Solution Approach 2:
Different regions of the workspace are assigned different safety characteristics and interaction permissions. The first safety zone allows closer interaction with stricter monitoring, while the second safety zone permits greater interaction freedom. This local differentiation resolves the contradiction by providing safety where needed while enabling interaction where appropriate.
2Productivity
If sophisticated 3D sensing and analysis approaches are used to allow closer human-machine collaboration, then productivity is improved, but it becomes difficult for human operators to evaluate the potential impact of their actions
Solution Approach 1:
The system provides continuous feedback to operators through perceptible signals (visual, auditory, or haptic) that indicate the current safety state and potential impacts of their actions. This feedback loop maintains operator understanding despite the complexity of the 3D sensing and analysis system, resolving the information loss problem while enabling close collaboration.
Solution Approach 2:
The system uses color-coded signaling (e.g., different colors for different safety zones or risk levels) to provide intuitive visual feedback to operators about the system state and potential impacts of their actions. This makes the complex 3D sensing data easily interpretable, maintaining operator understanding while enabling close human-machine collaboration.
Data Source
AI summary
Systems and methods for determining safe and unsafe zones in a workspace—where safe actions are calculated in real time based on all relevant objects (e.g., some observed by sensors and others computationally generated based on analysis of the sensed workspace) and on the current state of the machinery (e.g., a robot) in the workspace—may utilize a variety of workspace-monitoring approaches as well as dynamic modeling of the robot geometry. The future trajectory of the robot(s) and/or the human(s) may be forecast using, e.g., a model of human movement and other forms of control. Modeling and forecasting of the robot may, in some embodiments, make use of data provided by the robot controller that may or may not include safety guarantees.