Dynamic Critical Distance Control for Collaborative Robot Safety
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Solution Overview
Problem
In collaborative robotic work environments without physical fences, setting a uniform critical distance for workers of varying skill levels and environments can lead to safety risks and reduced workability, as highly skilled workers may approach robots too closely while low-skilled workers may collide with them, and environmental conditions like post-mealtime distractions increase risk.
Innovation Solution
A robot safety system that acquires personal and environmental information to dynamically set critical distances for each worker, using a critical distance setting unit that adjusts based on individual skill levels, age, experience, and real-time physical conditions, and includes a monitor system to alert workers and supervisors when distances become unsafe.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a uniform critical distance is set for all workers, then the safety of low-skilled workers is improved, but the workability of highly-skilled workers deteriorates
Solution Approach 1:
The critical distance is made dynamic rather than uniform. The system automatically adjusts the critical distance for each worker based on their skill level, allowing highly-skilled workers to have shorter critical distances (improving workability) while low-skilled workers have longer critical distances (maintaining safety). This resolves the contradiction by making the safety parameter adaptive to individual worker capabilities.
Solution Approach 2:
The system changes the parameter of critical distance based on worker attributes. By evaluating worker skill levels and adjusting the critical distance parameter accordingly, the system optimizes both safety and workability. Highly-skilled workers receive smaller critical distance values while less experienced workers receive larger values, eliminating the need for a one-size-fits-all approach.
2Reliability
If a long critical distance is set to ensure safety, then the safety of all workers is improved, but the time to approach the robot increases
Solution Approach 1:
The critical distance becomes a dynamic parameter that adjusts based on real-time worker evaluation. Experienced workers who can approach quickly and safely have their critical distance reduced, minimizing approach time. Less experienced workers maintain longer critical distances for safety. This dynamic adjustment resolves the time-safety contradiction by optimizing the critical distance for each worker's capability.
Solution Approach 2:
The system changes the critical distance parameter based on worker evaluation results. By modifying this parameter according to individual worker skills and performance, the system achieves both safety and efficiency. Workers who demonstrate competence receive parameter adjustments that reduce unnecessary waiting time while maintaining adequate safety margins.
3Productivity
If a short critical distance is set to improve workability, then the approach time to the robot is reduced, but the safety risk for low-skilled workers increases
Solution Approach 1:
The system applies different critical distance values to different workers based on their local characteristics (skill level, experience). Instead of a global uniform setting, each worker receives a customized critical distance that matches their capability. This local quality approach allows highly-skilled workers to benefit from shorter distances while protecting less experienced workers with longer distances.
Solution Approach 2:
The critical distance parameter is modified based on worker evaluation. The system automatically adjusts this parameter for each worker, assigning smaller values to highly-skilled workers (improving workability) and larger values to less experienced workers (maintaining safety). This parameter differentiation resolves the contradiction between workability and safety.
4Reliability
If the critical distance is adjusted based on worker skill level, then both safety and workability are improved, but the system complexity increases
Solution Approach 1:
The system performs self-evaluation of worker skill levels and automatically adjusts critical distances without requiring complex manual configuration. The evaluation unit assesses worker capabilities and the control unit automatically modifies parameters, making the system self-regulating. This reduces the operational complexity despite the advanced functionality.
Solution Approach 2:
The system integrates multiple functions into a unified platform: worker evaluation, critical distance calculation, real-time monitoring, and automatic parameter adjustment. By combining these functions into a single multi-functional system, the patent avoids the complexity that would arise from separate independent systems while achieving comprehensive safety and workability optimization.
Data Source
AI summary
A system to secure people's safety in places such as a factory wherein people and industrial robot collaborate with each other in a state that a physical fence surrounding the preferred industrial robot's working region is excluded. The system is capable of acquiring respective distances between robot and a plurality of people. Furthermore, a critical distance of each person is set on the basis of at least one of personal information that each person individually has and environment information to be set depending on the robot's setting environment. A mounted-type monitor is respectively mounted on the plurality of people and is capable of displaying information within a view of each person, and a control unit is capable of controlling display content thereon. According to the display control, when a distance between robot and each person becomes less than a critical distance, the distance state is displayed on the mounted-type monitor.