Full Jacobian: The resulting returned jacobian can be thought of as a set of several concatenated jacobians as follows: [ J_multisensor_0 ] J = [ J_multisensor_1 ] [ : ] [ J_multisensor_M ] where M is the number of multisensors, which is generally the number of calibration samples collected. Multisensor Jacobian: The Jacobian for a given multisensor is created by concatenating jacobians for each sensor [ J_sensor_m_0 ] J_multisensor_m = [ J_sensor_m_1 ] [ : ] [ J_sensor_m_S ] where S is the number of sensors in this multisensor. Sensor Jacobian: A single sensor jacobian is created by concatenating jacobians for the system parameters and checkerboards J_sensor_m_s = [ J_params_m_s | J_m_s_pose0 | J_m_s_pose1 | --- | J_m_s_CB_poseC ] The number of rows in J_sensor_m_s is equal to the number of rows in this sensor's residual. J_params_m_s shows how modifying the free system parameters affects the residual. Each J_m_s_pose_c is 6 columns wide and shows how moving a certain target affects the residual. All of the J_m_s_pose blocks are zero, except J_sensor_pose_m, since target m is the only target that was viewed by the sensors in this multisensor.
Generates the jacobian from a target pose to the multisensor's residual. Input: - opt_param_vec: Vector of the free system parameters (the parameters we're actuall optimizing) - pose_param_vec: Vector of length 6 encoding the target's pose 0:3=translation 3:6=rotation_axis - multisensor: The actual multisensor definition. Output: - J_scaled: An mx6 jacobian, where m is the length of multisensor's residual. There are 6 columns since the target's pose is encoded using 6 parameters. If covariance calculations are enabled, then the Jacobian is scaled by sqrt(Gamma), where Gamma is the information matrix for this measurement.
Computes the jacobian from the free system parameters to a single sensor Inputs: - opt_param_vec: Vector of the free system parameters (the parameters we're actuall optimizing) - target_pose_T: The pose of the target that this sensor is viewing - target_id: String name of the target that this sensor is viewing. This is necessary to generate the set of feature points on the target - sensor: The actual sensor definition Output: - J_scaled: An mxn jacobian, where m is the length of sensor's residual and n is the length of opt_param_vec. If covariance calculations are enabled, then the Jacobian is scaled by sqrt(Gamma), where Gamma is the information matrix for this measurement.