7. Tuning & Optimization

The tuning and optimization process represents a critical phase in robotics development where teams systematically refine their robot's performance through real-time parameter adjustments.

Configuration Process

The tuning setup requires configuration in both the Elastic environment and Advantage Scope to establish a proper communication pipeline. Begin by selecting "localhost" within the Elastic interface to designate the local machine as the primary connection point for tuning data.

Next, activate the "DebugGroup" within Elastic to expose the tuning parameters to the external tuning interface. This debug group acts as a container for all tunable values, providing organizational structure while ensuring that only designated parameters are accessible for real-time modification. The grouping mechanism helps maintain system safety by preventing accidental modification of critical system parameters that shouldn't be adjusted during operation.

Within Advantage Scope, navigate to the tuning configuration section and enable the tuning functionality. This action establishes the bidirectional communication link between Advantage Scope and the robot code, allowing parameter changes made in the interface to be immediately transmitted to the running robot system.

Update Parameters in Code

After tuning parameters in Advantage Scope, it is essential to update these values in your program to ensure they persist across deployments. Locate the section of your code where the tuned parameters are defined, and replace the old values with the new ones obtained during the tuning process.

Once the updated values are saved in your program, redeploy the code to the robot. This ensures that the tuned parameters are now part of the robot's default configuration and will be used during subsequent operations, even after a restart or power cycle.

By following this process, you maintain consistency between the tuned values and the deployed code, preventing the need to retune parameters unnecessarily.