3D 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
1Productivity
If conventional industrial robots are used for manufacturing, then productivity and quality are improved, but safety for human operators deteriorates due to unpredictable movements and lack of precise control
Solution Approach 1:
The system continuously monitors robot position, velocity, and acceleration through sensors and feeds this information back to the safety controller. The controller compares actual trajectory against the pre-calculated safety envelope and dynamically adjusts robot operation to maintain safe separation distances, resolving the contradiction between maintaining productivity and ensuring operator safety.
Solution Approach 2:
Before robot operation begins, the system pre-calculates the safety envelope based on robot kinematics, dynamics, and worst-case stopping distances. This preliminary safety model is established offline, allowing the robot to operate at full speed within defined boundaries without continuous safety interruptions, thus maintaining productivity while preventing harm.
2Productivity
If robot speed and acceleration are increased to improve productivity, then manufacturing output increases, but stopping distance and safety control deteriorate
Solution Approach 1:
The system transitions from considering only spatial position to incorporating temporal dimensions by calculating safety envelopes that account for robot acceleration, velocity, and stopping time. The safety model operates in space-time, defining not just where the robot can be but also how long it takes to stop from any position, enabling high-speed operation with guaranteed safety margins.
Solution Approach 2:
The safety envelope is dynamically adjusted based on real-time robot state. When the robot operates at higher speeds, the safety controller increases separation distances and adjusts acceleration limits. The system continuously adapts safety parameters to match current operating conditions, allowing maximum productivity while maintaining adequate stopping distances.
3Manufacturing precision
If robot accuracy is improved through better manufacturing tolerances and control, then positioning precision increases, but system complexity and cost increase
Solution Approach 1:
The system introduces a mathematical safety envelope model as an intermediary between the robot controller and safety requirements. Rather than modifying the robot hardware for higher accuracy, the software model compensates for positioning uncertainties by calculating appropriate safety margins. This intermediary layer achieves safety without requiring complex hardware modifications.
Solution Approach 2:
The system changes safety parameters (separation distances, velocity limits, acceleration limits) based on actual robot performance characteristics rather than assuming worst-case scenarios. By measuring and utilizing actual positioning accuracy, the system optimizes safety margins to be no larger than necessary, reducing unnecessary constraints on productivity while maintaining safety.
4Object-affected harmful factors
If light curtains or 2D area sensors are used for safety monitoring, then human-robot separation is enforced, but workspace collaboration flexibility deteriorates
Solution Approach 1:
The safety system transitions from static safety zones to dynamic safety envelopes that move with the robot. The safety model continuously updates the protected volume based on robot position, orientation, and velocity, allowing humans to work in areas that are safe at any given moment. This dynamic approach enables flexible human-robot collaboration while maintaining protection, unlike fixed light curtains that constrain the workspace.
Data Source
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Figure 3A~3C
AI summary
A method of enforcing safe operation of machinery in a 3D workspace comprises storing a model of the machinery, its permitted movements and a safety protocol. A first 3D region of the workspace is mapped, corresponding to space occupied by the machinery augmented by a 3D envelope spanning all movements executed by the machinery. A second 3D region is mapped, corresponding to a portion of the first 3D region predictively occupied by the machinery during an interval. A third 3D region is identified, corresponding to space occupied or potentially occupied by a human augmented by a 3D envelope corresponding to anticipated movements of the human during the interval. Operation of the machinery is restricted in accordance with the safety protocol based on proximity between the second and third regions.