Robot simulation tests are essential for verifying the performance, reliability, and safety of robotic systems before deploying them in real-world scenarios. However, simulation tests also pose some risks and challenges that need to be addressed carefully. In this article, you will learn how to ensure robot simulation tests are safe by following some best practices and guidelines.
The first step to ensure robot simulation tests are safe is to choose the right simulation software for your specific needs and goals. There are many simulation software available, such as Gazebo, V-REP, and Webots, that offer different features, capabilities, and compatibility. You should consider factors such as the level of realism, the complexity of the environment, the type of robot, the programming language, and the hardware requirements when selecting the simulation software. You should also check the documentation, support, and community of the software to ensure its quality and reliability.
Right simulation tools is really matter but not according to brand based pick up. Correct simulation tool must be related to the goal and simulation scope. You need to understand what the questions are? Are the robot is safe while it is moving? Or are the robots are safe enough while they are working together? Or are the robot is safe enough to cooperate with an human. These 3 questions are actually referring 3 different scope. For example first one targets the robot and the environment interaction. In this case you should pick up a software you can test and verify that robot sensors read a data from the environment variables. Then you can check that the software whether support the type of the sensors you need.
The second step to ensure robot simulation tests are safe is to validate the simulation model against the real robot and the physical environment. This means that you should compare the simulation results with the actual measurements and observations to verify that the simulation model accurately represents the robot's behavior, dynamics, and interactions. You should also test the simulation model under different conditions and scenarios to ensure its robustness and stability. You should use appropriate validation methods and metrics, such as error analysis, sensitivity analysis, and uncertainty quantification, to evaluate the simulation model.
Once you find the right scope of simulation related the goal, model validation can be more precise. For example if your goal is make sure 2 of your robots have to work together without collision, you have to be sure that virtual layout and real layout are the same. Best practice is here you can use a reference frame as one of your robot's base then you can write a small robot program for your robot to move it to a specific place like a door frame or wall corner or touch a corner of a table. You can also design a specific toolings for this. After you run the real robot in real world, measure the difference of the movement with virtual twin and relocate everything in the simulation according to this difference.
The third step to ensure robot simulation tests are safe is to implement safety measures to prevent or mitigate potential hazards and damages. For example, you should use a kill switch or an emergency stop button to terminate the simulation test in case of any unexpected or dangerous situation. You should also monitor the robot's state and performance during the simulation test and check for any signs of overheating, malfunctioning, or collision. You should also follow the safety standards and regulations for robot simulation tests, such as ISO 10218 and ISO/TS 15066, to ensure the safety of the human operators and the environment.
In this stage, I always suggest to make a Virtual commissioning(VC) to be ensure how the virtual robots will react to the realistic scenarios. You can never imagine what can go wrong with the real implementations. To me VC is using real controllers and indicators to control virtual robots in their virtual environments. Imagine that your joystick is real, your virtual robot is running in simulations, and a virtual lidar sensor is triggered because of an event happened in the simulation. Then you get alert by real indicators such as a light stack on your desk. In this way you can measure what is your robot reaction time and measure your lidars coverage zone.
The fourth step to ensure robot simulation tests are safe is to review the simulation data and analyze the outcomes and implications. You should collect and store the simulation data in a secure and organized way, using appropriate formats, tools, and databases. You should also process and visualize the simulation data to identify any patterns, trends, or anomalies that might indicate a problem or an opportunity. You should also interpret and communicate the simulation data to the relevant stakeholders and users, using clear and concise reports, graphs, and charts.
The fifth step to ensure robot simulation tests are safe is to update the simulation model based on the feedback and findings from the previous steps. You should use the simulation data to calibrate, refine, and improve the simulation model to increase its accuracy, reliability, and efficiency. You should also use the simulation data to optimize, debug, and enhance the robot's functionality, performance, and behavior. You should also use the simulation data to explore new possibilities, scenarios, and features for the robot's design, development, and deployment.
The sixth and final step to ensure robot simulation tests are safe is to repeat the simulation test with the updated simulation model and verify the results and improvements. You should run the simulation test again with the same or different parameters, conditions, and goals to evaluate the impact and effectiveness of the changes and modifications. You should also compare the simulation test results with the previous ones and with the real robot and the physical environment to validate the simulation model. You should also document and report the simulation test results and the simulation model updates to ensure transparency and accountability.