Abstract: A simulation system may generate radar data for synthetic simulations of autonomous vehicles, by using a data store of object radar data and attributes determined from sensor data captured in real-world physical environments. The radar data store may include radar point clouds representing real-world objects and associated object attributes, as well as radar background data captured for a number of physical environments. The simulation system may construct radar data for use in a simulation based on radar object data and/or radar background data, including using various probabilities within various overlay regions to determine subsets of object and background radar points to be rendered. During a simulation, the generated radar data may be provided to a simulated radar sensor of a simulated vehicle configured to execute trained perception models based on radar data input.

Abstract: A simulation system may generate radar data for synthetic simulations of autonomous vehicles by determining and applying radar masks for object radar data based on the attributes of simulated objects. A simulation system may determine a simulated object within a region of a simulated environment, and may apply a radar mask to determine the radar data within the region based on attributes of the simulated object. Such attributes may include the material properties, object type, and/or distance of the simulated object from the simulation sensors. Radar masks may be determining using masking percentages based on combinations of object attributes, and masks may be applied individually or by combining multiple masks for multiple occluding objects, in order to more accurately simulate the behavior of real-world radar signals in autonomous vehicle simulations.

Abstract: A simulation system may generate radar data for synthetic simulations of autonomous vehicles, by using a data store of object radar data and attributes determined from sensor data captured in real-world physical environments. The radar data store may include radar point clouds representing real-world objects and associated object attributes, as well as radar background data captured for a number of physical environments. The simulation system may construct radar data for use in a simulation based on radar object data and/or radar background data, including using various probabilities within various overlay regions to determine subsets of object and background radar points to be rendered. During a simulation, the generated radar data may be provided to a simulated radar sensor of a simulated vehicle configured to execute trained perception models based on radar data input.

Abstract: A simulation system may generate radar data for synthetic simulations of autonomous vehicles, by using a data store of object radar data and attributes determined from sensor data captured in real-world physical environments. The radar data store may include radar point clouds representing real-world objects and associated object attributes, as well as radar background data captured for a number of physical environments. The simulation system may construct radar data for use in a simulation based on radar object data and/or radar background data, including using various probabilities within various overlay regions to determine subsets of object and background radar points to be rendered. During a simulation, the generated radar data may be provided to a simulated radar sensor of a simulated vehicle configured to execute trained perception models based on radar data input.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.

Abstract: A sensor simulation system may generate sensor data for use in simulations by rendering two-dimensional views of a three-dimensional simulated environment. In various examples, the sensor simulation system uses sensor dependency data to determine specific views to be re-rendered at different times during the simulation. The sensor simulation system also may generate unified views with multi-sensor data at each region (e.g., pixel) of the two-dimensional view for consumption by different sensor types. A hybrid technique may be used in some implementations in which rasterization is used to generate a view, after which ray tracing is used to align the view with a particular sensor. Spatial and temporal upsampling techniques also may be used, including depth-aware and velocity-aware analyses for simulated objects, to improve view resolution and reduce the frequency of re-rendering views.