…e we actually have data points when we first call fit_sphere(...) which prevents three numpy RuntimeWarnings (we were sometimes calling np.std on an empty list)

…. Speeds up computation but potentially reduces accuracy. Needs testing

…r the next sphere_fit. Speeds up computation time

…antly faster), and fix parameter from launch file

…s execution time being too long (the number of msgs recieved was system-dependant and made it impossible to compare accuracy of calibration fits between runs). Modified code to save all tf messsages and process them in get_knuckle_positions. Added code to load a bag file for testing/tuning/comparing accuracy of calibration fits. Now that _load_tf_callback is recieving all the messages, the average number of msgs per second has gone up from ~15 to ~100, drastically increasing the computation of sphere fit. But, now we can add code to downsample to a KNOWN number of 'datapoints per second', giving the same performance across systems and lettings us actually figure out how many datapoints per second we need for a reasonable calibration fit

…pling to approximately a 'known' number of samples-per-second. Switched to MarkerArrays for faster marker publishing. Also general tidying

… with a bag

…adow-robot/polhemus_ros_driver into F_#HE_948_improve_calibration_process