A camera measurement model and a camera detection model have been added. Typical sensors that can use these models: Raw camera images preprocessing units, e.g. image detectors, classifiers or deep learning algorithms.
Efficient data fusion development for ADAS and automated driving
BASELABS Create is designed for the fast development of complex data fusion algorithms. BASELABS Create can be used with field-tested, pre-implemented algorithms as well as for the development of fully custom algorithms.
Camera measurement and detection models
Radar detection model
A radar detection model has been added to describe the detection capabilities of radar sensors whose field of view is given by a circular ring sector. Typical sensors that can use this model:
Smart sensor models
For smart sensors, multiple measurement and detection models have been added. Among others, these models can be used for the sensors:
Constant acceleration model
A motion model has been added that estimates the acceleration of an object in addition to its position and velocity.
Visual Studio item templates
Visual Studio item templates for creating new measurement models, detection models, track proposers, track removers and system models.
Improved radar measurement model
The radar measurement model now supports rotated sensors and incorporates the yaw rate of the ego vehicle to further improve the model accuracy and to increase its applicability in urban scenarios.
- Fixed: Biased calculation of the covariance in the SampleSet.ToGaussian() method
- Fixed: BayesFilter.Predict() returns wrong results
- Fixed: Race condition in licensing
- Fixed: PersitenceModel.Evaluate() returns negative values for retrodiction
- Fixed: Call for Evaluate() on system models leads to numeric exception
- Fixed: License Exception in vADASdeveloper connection designer when GhostDoc is installed
- Fixed: Usage of BASELABS Create with folder path including symbols such as "#"
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Figure 1. Former implementation of the PredictXAndReset method. The example of the ego motion estimation is shown for the case of Unscented Kalman Filter (UKF) based implementation.