Avular is working on a product that uses radar and stereovision technology for the autonomous navigation of mobile robots and drones. Before our clients can start using this navigation solution, we need to prove that its software is safe. This is challenging, since no functional safety norm exists for software. Avular will use the RobMoSys approach in software development. This ensures that the programming work is carried out in a well-defined and neat way. Thereby limiting the likelihood of errors and allowing to estimate its performance.
Avular’s new navigation solution relies on the combination of radar data with stereovision data. As these technologies are complementary, they are the perfect match to generate reliable data in a large variety of circumstances, allowing for autonomous navigation and SLAM (simultaneous navigation and mapping). Thanks to the low hardware costs of this technology, this navigation solution will have a way lower price than existing LiDar-based solutions. On top of that, our new product can be used in bad weather conditions and dusty areas, which is not possible with LiDar technology. Based on viability study into this product *make link to SPANAR page*, Avular sees a large application potential for this product, that has the potential to disrupt the mobile robotics market.
High quality and reliable stereovision cameras and radar chips can be bought off the shelf and serve as the starting point for this navigation solution. The way in which our engineers combine the output of these technologies is where the real magic happens. This is done through a complex sensor fusion approach that merges the point cloud data from the radar, with the more detailed data from the stereovision camera to obtain reliable depth maps of the robot’s surroundings. These fused depth maps are used for SLAM and autonomous navigation.
To ensure that robots that use this navigation solution navigate safely, we need to show that the software and the depth maps resulting from it are safe. normally, functional safety can be tested using safety standards, but these do not exist for software.
In May 2020, Avular received funding from the RobMoSys project. RobMoSys is a model-based approach for robotics, that allows to build better defined systems. In our case, we use it to make the first steps towards proving safety of our software. In this project, we will establish a RobMoSys conformant formal framework of the fusion software and use statistics derived from in-field measurements to reliably predict accuracy of the resultant depth map. This output along with the software architecture can be used to give a first estimate of the safety integrity level (SIL) of the software. Next steps will include safety certification of the product, but this is not part of the current project.
Currently, it is up to our software engineers to construct the sensor fusion software in a RobMoSys conformant way and to make the first estimates of its performance and safety.
To be continued.
Subsidy: RobMoSys (Horizon2020)