In a first version, we could just add the ground truth for the cones observations.
In a second version, we could add noises to these observations and add parameters to choose from several noise models (gaussian, uniform, exponential, etc.).
Implementation
Parameters
cones_observations_freq: float
cones_observations_range_noise_model: string
cones_observations_bearing_noise_model: string (in "uniform", "uni","exponential","exp","normal", "gaussian")
cones_observations_range_noise_param: float (either max value for uniform (symmetric support), 1/mean for exp, std for normal)
ihm2/mgs/ConesObservations: based on the following .msg file:
# ConesObservations
std_msgs/Header header
uint8 BLUE = 0
uint8 YELLOW = 1
uint8 SMALL_ORANGE = 2
uint8 BIG_ORANGE = 3
float64[] rho
float64[] theta
uint8[] colors
float64[] rho_uncertainty # std dev of the rho (range) measurement
float64[] theta_uncertainty # std dev of the theta (bearing) measurement
float64[] colors_confidence # confidence of the color measurement, between 0 and 1
Goal
In a first version, we could just add the ground truth for the cones observations. In a second version, we could add noises to these observations and add parameters to choose from several noise models (gaussian, uniform, exponential, etc.).
Implementation
Parameters
cones_observations_freq: floatcones_observations_range_noise_model: stringcones_observations_bearing_noise_model: string(in"uniform","uni","exponential","exp","normal","gaussian")cones_observations_range_noise_param: float(either max value for uniform (symmetric support), 1/mean for exp, std for normal)cones_observations_bearing_noise_param: floatPublishers
/ihm2/cones_observations: ihm2/msg/ConesObservationsCustom interfaces
ihm2/mgs/ConesObservations: based on the following.msgfile: