sensor-simulation

Configure camera and LIDAR sensors by defining SDF sensor elements on your robot model with parameters like resolution, field of view, range, and update rates. Gazebo publishes sensor data to ROS topics for perception algorithms to consume.

Resolution, field of view, range, update rates, and noise models directly impact realism. Adjusting these parameters lets you simulate real-world sensor behavior like blur, range limits, and measurement noise for algorithm testing.

Yes. IMU and contact sensors are configured in SDF the same way as camera and LIDAR—by specifying sensor blocks with appropriate parameters and topic names. Gazebo publishes their data streams for perception workflows.

Enable sensor visualization in Gazebo to see camera feeds and LIDAR point clouds. Monitor ROS topics to verify data publication, check update rates, and inspect noise parameters to identify configuration or physics issues.

Gazebo supports configurable noise models for each sensor type. Apply realistic noise parameters that match your target hardware to test perception algorithm robustness before deployment on physical robots.

ROS integration is optional but recommended. It provides standard topic naming conventions and middleware for routing sensor data to perception stacks, though Gazebo can publish sensor data independently.