Telemetry Panel

The Telemetry Panel in the GRID Platform is designed to help users analyze and understand the performance and behavior of their simulations. This panel allows users to replay telemetry data from previous simulation runs, providing valuable insights and enabling detailed examination of the simulation's dynamics. The telemetry feature in GRID is powered by Rerun.

Key features of the Rerun Telemetry Panel include:

  • Realtime Telemetry Data: Users can display and visualize telemetry data from the current simulation sessions, allowing them to review and analyze the performance of their robots and AI models.

  • Data Visualization: The panel provides various visualization tools to help users interpret telemetry data, including images, 3D point clouds, and 1D streams of time series data such as IMU data.

  • Comparative Analysis: The panel allows users to compare telemetry data from different entities such as different operating conditions, different AI models etc. runs, making it easier to spot trends and evaluate the impact of changes to their code.

  • Export Data: Users can export telemetry data for further analysis or reporting, ensuring that valuable insights are not lost.

To access the Rerun Telemetry Panel, navigate to the I/O panel and select the telemetry visualization tab.

Users can follow the Rerun API to log data into the telemetry panel. For example, to log a random image to telemetry, the code would look as follows:

import numpy as np
import rerun as rr

# Create a random 256x256 image
random_image = np.random.randint(0, 256, (256, 256, 3), dtype=np.uint8)

# Log the image to the telemetry panel
rr.log_image("grid/random_image", random_image)