Perirobot space representation for HRI: measuring and designing collaborative workspace coverage by diverse sensors

TL;DR

This paper introduces a unified occupancy-based representation for sensor coverage in human-robot interaction spaces, enabling effective comparison and optimization of sensor setups for safety and perception.

Contribution

It proposes a novel occupancy-based framework to represent and evaluate sensor coverage in HRI environments, facilitating sensor placement and system design.

Findings

Occupancy representation effectively compares sensor coverage.

Sensor setup optimization improves workspace safety.

Framework applicable to static and dynamic scenes.

Abstract

Two regimes permitting safe physical human-robot interaction, speed and separation monitoring and safety-rated monitored stop, depend on reliable perception of the space surrounding the robot. This can be accomplished by visual sensors (like cameras, RGB-D cameras, LIDARs), proximity sensors, or dedicated devices used in industrial settings like pads that are activated by the presence of the operator. The deployment of a particular solution is often ad hoc and no unified representation of the interaction space or its coverage by the different sensors exists. In this work, we make first steps in this direction by defining the spaces to be monitored, representing all sensor data as information about occupancy and using occupancy-based metrics to calculate how a particular sensor covers the workspace. We demonstrate our approach in two (multi-)sensor-placement experiments in three static scenes and one experiment in a dynamic scene. The occupancy representation allow to compare the effectiveness of various sensor setups. Therefore, this approach can serve as a prototyping tool to establish the sensor setup that provides the most efficient coverage for the given metrics and sensor representations.