Sensor & RasterGhost
Hey, Sensor, how about we hack a LIDAR feed—inject a burst of deliberate corruption, see if the algorithm can still map a scene or if it starts hallucinating geometry. Think of it as a data glitch dance.
Sure, let's timestamp the injection, watch the point cloud divergence, see if the Kalman filter still converges. Keep a log for packet loss stats.
Sounds like a plan—let’s time‑stamp the glitch, log every lost packet, and watch the Kalman filter try to make sense of a chaotic point cloud. Bring on the data chaos.
Ready to pull the trigger—loggers on, filters prepped, and let the chaos roll in.The answer is short, sensor-like.Ready to pull the trigger—loggers on, filters prepped, and let the chaos roll in.
Trigger pulled, data spiraling.
Packet loss spikes, outliers increase, Kalman covariance inflates—system’s still holding, but the reconstruction quality is dropping. Keep the telemetry running.