Abstract
We introduce a novel simulation-based approach to identify hazards that result from unexpected worker behavior in human-robot collaboration. Simulation-based safety testing must take into account the fact that human behavior is variable and that human error can occur. When only the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">expected</i> worker behavior is simulated, critical hazards can remain undiscovered. On the other hand, simulating <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">all</i> possible worker behaviors is computationally infeasible. This raises the problem of how to find <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">interesting</i> (i.e., potentially hazardous) worker behaviors given a limited number of simulation runs. We frame this as a search problem in the space of possible worker behaviors. Because this search space can get quite complex, we introduce the following measures: (1) Search space restriction based on workflow-constraints, (2) prioritization of behaviors based on how far they deviate from the nominal behavior, and (3) the use of a risk metric to guide the search towards high-risk behaviors which are more likely to expose hazards. We demonstrate the approach in a collaborative workflow scenario that involves a human worker, a robot arm, and a mobile robot.
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