Potential Occupancy Envelopes for Safe Human-Robot Collaboration
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Solution Overview
Problem
Conventional industrial robots are unsafe for human-robot collaboration due to limited accuracy and dynamic modeling, leading to potential injuries from unpredictable movements and lack of precise control over stopping distances, especially in complex tasks or varying environmental conditions.
Innovation Solution
A safety system that models potential occupancy envelopes (POEs) of robots and humans in a 3D workspace, using sensors and simulation to dynamically restrict robot movements and ensure safe separation distances, allowing for real-time updates and visualization of safe/unsafe regions to prevent collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If conventional industrial robots are used with fixed positions and powerful arms, then productivity and strength are improved, but safety deteriorates due to large stopping distances and unpredictable movements in collaborative workspaces
Solution Approach 1:
The patent applies dynamics by making the robot's operational parameters adaptive rather than fixed. The system continuously monitors the workspace environment and dynamically adjusts the robot's speed, acceleration, and stopping distance based on the presence and position of humans. This allows the robot to maintain full power and speed when the workspace is clear, while automatically reducing power and increasing stopping distances when humans are detected, thus resolving the contradiction between strength and safety
Solution Approach 2:
The patent implements feedback through continuous monitoring of the workspace using sensors that detect human presence, position, and movement. This feedback loop provides real-time information to the control system, which then adjusts robot operations accordingly. The system measures actual stopping distances and uses this information to refine safety parameters, creating a closed-loop control system that balances productivity and safety through continuous adaptation
2Productivity
If robot speed and acceleration are increased to improve productivity, then manufacturing output increases, but positioning accuracy deteriorates due to inertia and dynamic effects
Solution Approach 1:
The patent addresses this contradiction by implementing dynamic parameter adjustment based on real-time conditions. The control system continuously adapts the robot's speed and acceleration profiles according to the task requirements and environmental conditions. For high-productivity tasks where precision requirements are lower, the system allows higher speeds and accelerations, while for tasks requiring high precision, it automatically reduces dynamic parameters to maintain positioning accuracy, thus resolving the trade-off between productivity and precision
Solution Approach 2:
The patent applies parameter changes by systematically varying operational parameters such as speed, acceleration, and positioning tolerance based on the specific task and environmental conditions. The system adjusts these parameters dynamically rather than maintaining fixed values, allowing optimal performance across different operating conditions. This enables the robot to achieve high productivity when appropriate while maintaining sufficient precision when required
3Reliability
If traditional guarding methods like cages or light curtains are used to ensure safety, then human protection is improved, but workspace flexibility and collaboration capability deteriorate
Solution Approach 1:
The patent replaces mechanical guarding systems (cages, physical barriers) with an intelligent software-based control system that uses sensors, computer vision, and real-time processing to detect human presence and adjust robot operations accordingly. This substitution eliminates the need for physical barriers while maintaining safety, thereby preserving workspace flexibility and enabling true human-robot collaboration. The system provides equivalent or superior protection compared to mechanical guarding while allowing unrestricted access to the workspace
Data Source
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Figure 3A~3C
AI summary
A system for spatially modeling a workspace comprises a robot controller (1004) having a safety-rated component (1006) and a non-safety-rated component (1008). The system further comprises an object-monitoring system configured to computationally generate a first potential occupancy envelope for a robot (1002) and a second potential occupancy envelope for a human operator when performing a task in the workspace (1000). A first set of stored instructions is executable by the non-safety-rated component (1008) of the controller for causing execution by the robot of a programmed task. A second set of stored instructions is executable by the safety-rated component (1006) of the controller for stopping or slowing the robot. The object-monitoring system detects a predetermined degree of proximity between the first and second potential occupancy envelopes and causes the controller to put the robot in a safe state.