Systematic and Realistic Testing in Simulation of Control Code for Robots in Collaborative Human-Robot Interactions

TL;DR

This paper presents a systematic simulation-based testing approach using Coverage-Driven Verification for verifying robotic control code in human-robot interaction scenarios, enhancing safety and reliability.

Contribution

It introduces a two-tiered test generation method combined with CDV for realistic and automated robot code testing in simulation environments.

Findings

High automation in simulation-based verification achieved.

Systematic test generation improves exploration of robot code.

Effective testing of human-robot interaction scenarios demonstrated.

Abstract

Industries such as flexible manufacturing and home care will be transformed by the presence of robotic assistants. Assurance of safety and functional soundness for these robotic systems will require rigorous verification and validation. We propose testing in simulation using Coverage-Driven Verification (CDV) to guide the testing process in an automatic and systematic way. We use a two-tiered test generation approach, where abstract test sequences are computed first and then concretized (e.g., data and variables are instantiated), to reduce the complexity of the test generation problem. To demonstrate the effectiveness of our approach, we developed a testbench for robotic code, running in ROS-Gazebo, that implements an object handover as part of a human-robot interaction (HRI) task. Tests are generated to stimulate the robot's code in a realistic manner, through stimulating the human, environment, sensors, and actuators in simulation. We compare the merits of unconstrained, constrained and model-based test generation in achieving thorough exploration of the code under test, and interesting combinations of human-robot interactions. Our results show that CDV combined with systematic test generation achieves a very high degree of automation in simulation-based verification of control code for robots in HRI.