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Robotec team will support in applying ROS and ROS2 middleware to develop your robotic applications. We provide expertise and software engineering services to implement systems based on ROS2.
Run accurate sensor simulation for cameras, LiDAR, radar, and UWB sensors on GPU. Our sensor engine enables matching the sensors' specifications and noise models, enabling thorough testing and validation.
Customized robotics simulation platforms based on Open 3D Engine and Unity3D. Apart from custom software engineering work we support development of digital twins, integrations (ROS 2 and proprietary stack), cloud services, AI/ML pipelines, multiple vehicle models (including non-standard specialized vehicles) and sensors modelling.
We selected and integrated LIDAR-based sensors setup in a truck. We worked on perception algorithms for obstacles detection using also novel machine-learning methods like point pillars.
Driver distraction detection is one of the most important DMS functions. We provide the expertise to develop distraction detection based on gaze vector calculations and safety critical areas of interest. Our team also work with Partners on distraction ground-truth datasets.
Drowsiness in one of the most challenging driver states to detect due to highly individualized behavioral symptoms. In our work we are going beyond eye closure metrics to support our Partners in developing next level drowsiness detection. We provide services related to the development of ground-truth datasets based on combination of multiple physiological (EEG, ECG) and driving performance measures.
DUI is one of the safety critical states that is expected from the future driver monitoring systems. We offer support in the state detection algorithms development as well as collecting and analyzing ground-truth datasets in laboratory conditions using driving simulators.
Our DMS team is supporting non-standard testing of near infrared (NIR) driver monitoring cameras. We offer standardized testing of NIR systems in multiple challenging lighting conditions (e.g. direct sunlight during sunset, bypassing vehicles with halogen lamps, zenith sunlight). We are analyzing transmittance of your windshield and NIR camera filters to provide a spectrum of scenarios your system is likely to encounter.
Dedicated driving simulator dataset collection campaign for generating ground truth datasets drowsiness detection. Our team applied a combination of eye closure metrics, driving performance and physiological data analysis (ECG and EEG).
Improve machine learning models' generalization through carefully crafted synthetic techniques. By utilizing simulated environments, we generate rich data comprising sensor readings like camera, lidar, or radar inputs. This data serves to augment existing datasets or create entirely new ones, effectively expanding the training data available for machine learning models.
Cloud simulation enables the generation of thousands of testing scenarios in a scalable way (large-scale and parallel). With the power of cloud simulation, we can effortlessly create thousands of testing scenarios at scale, leveraging parallel computing. Our deployment of simulation testing environments on Amazon Web Services (AWS) incorporates both AWS standard services and domain-specific tools like RoboMaker.
Our team developed proprietary machine learning solution for detecting anomaly behavior in the automotive application processor. Our work included preparation of the full AI pipeline including automated dataset generation and proprietary neural network architecture.
We love our job and exciting tech projects. We are building dedicated teams of passionate experts for our customers to deliver highest quality and smooth communication. We also believe in transparency and work ethics so your technical coordinators will be also well informed about our activities and progress.
Our software teams provide engineering support and training for our Customers. Support can be provided on-site or remotely depending on the project complexity and Customer needs.
