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

© Springer International Publishing Switzerland 2016. 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 humanrobot 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

Time-Aware Test Case Execution Scheduling for Cyber-Physical Systems

Testing cyber-physical systems involves the execution of test cases on target-machines equipped with the latest release of a software control system. When testing industrial robots, it is common that the target machines need to share some common resources, e.g., costly hardware devices, and so there is a need to schedule test case execution on the target machines, accounting for these shared resources. With a large number of such tests executed on a regular basis, this scheduling becomes difficult to manage manually. In fact, with manual test execution planning and scheduling, some robots may remain unoccupied for long periods of time and some test cases may not be executed. This paper introduces TC-Sched, a time-aware method for automated test case execution scheduling. TC-Sched uses Constraint Programming to schedule tests to run on multiple machines constrained by the tests’ access to shared resources, such as measurement or networking devices. The CP model is written in SICStus Prolog and uses the Cumulatives global constraint. Given a set of test cases, a set of machines, and a set of shared resources, TC-Sched produces an execution schedule where each test is executed once with minimal time between when a source code change is committed and the test results are reported to the developer. Experiments reveal that TC-Sched can schedule 500 test cases over 100 machines in less than 4 min for 99.5% of the instances. In addition, TC-Sched largely outperforms simpler methods based on a greedy algorithm and is suitable for deployment on industrial robot testing