Small updates in IMUKittiExampleVO
Luca Carlone
parent
d46902ea06
commit
0320baf3f7
|
|
@ -4,6 +4,7 @@ clc
|
|||
import gtsam.*;
|
||||
|
||||
%% Read metadata and compute relative sensor pose transforms
|
||||
% IMU metadata
|
||||
IMU_metadata = importdata('KittiEquivBiasedImu_metadata.txt');
|
||||
IMU_metadata = cell2struct(num2cell(IMU_metadata.data), IMU_metadata.colheaders, 2);
|
||||
IMUinBody = Pose3.Expmap([IMU_metadata.BodyPtx; IMU_metadata.BodyPty; IMU_metadata.BodyPtz;
|
||||
|
|
@ -12,20 +13,22 @@ if ~IMUinBody.equals(Pose3, 1e-5)
|
|||
error 'Currently only support IMUinBody is identity, i.e. IMU and body frame are the same';
|
||||
end
|
||||
|
||||
% VO metadata
|
||||
VO_metadata = importdata('KittiRelativePose_metadata.txt');
|
||||
VO_metadata = cell2struct(num2cell(VO_metadata.data), VO_metadata.colheaders, 2);
|
||||
VOinBody = Pose3.Expmap([VO_metadata.BodyPtx; VO_metadata.BodyPty; VO_metadata.BodyPtz;
|
||||
VO_metadata.BodyPrx; VO_metadata.BodyPry; VO_metadata.BodyPrz; ]);
|
||||
VOinIMU = IMUinBody.inverse().compose(VOinBody);
|
||||
|
||||
% GPS metadata
|
||||
GPS_metadata = importdata('KittiGps_metadata.txt');
|
||||
GPS_metadata = cell2struct(num2cell(GPS_metadata.data), GPS_metadata.colheaders, 2);
|
||||
GPSinBody = Pose3.Expmap([GPS_metadata.BodyPtx; GPS_metadata.BodyPty; GPS_metadata.BodyPtz;
|
||||
GPS_metadata.BodyPrx; GPS_metadata.BodyPry; GPS_metadata.BodyPrz; ]);
|
||||
|
||||
VOinIMU = IMUinBody.inverse().compose(VOinBody);
|
||||
GPSinIMU = IMUinBody.inverse().compose(GPSinBody);
|
||||
|
||||
%% Read data and change coordinate frame of GPS and VO measurements to IMU frame
|
||||
% IMU data
|
||||
IMU_data = importdata('KittiEquivBiasedImu.txt');
|
||||
IMU_data = cell2struct(num2cell(IMU_data.data), IMU_data.colheaders, 2);
|
||||
imum = cellfun(@(x) x', num2cell([ [IMU_data.accelX]' [IMU_data.accelY]' [IMU_data.accelZ]' [IMU_data.omegaX]' [IMU_data.omegaY]' [IMU_data.omegaZ]' ], 2), 'UniformOutput', false);
|
||||
|
|
@ -38,6 +41,7 @@ g = [0;0;-9.8];
|
|||
w_coriolis = [0;0;0];
|
||||
clear imum
|
||||
|
||||
% VO data
|
||||
VO_data = importdata('KittiRelativePose.txt');
|
||||
VO_data = cell2struct(num2cell(VO_data.data), VO_data.colheaders, 2);
|
||||
% Merge relative pose fields and convert to Pose3
|
||||
|
|
@ -50,23 +54,21 @@ VO_data = rmfield(VO_data, { 'dtx' 'dty' 'dtz' 'drx' 'dry' 'drz' });
|
|||
noiseModelVO = noiseModel.Diagonal.Sigmas([ VO_metadata.RotationSigma * [1;1;1]; VO_metadata.TranslationSigma * [1;1;1] ]);
|
||||
clear logposes relposes
|
||||
|
||||
% GPS data
|
||||
GPS_data = importdata('KittiGps.txt');
|
||||
GPS_data = cell2struct(num2cell(GPS_data.data), GPS_data.colheaders, 2);
|
||||
|
||||
% Convert GPS from lat/long to meters
|
||||
[ x, y, ~ ] = deg2utm( [GPS_data.Latitude], [GPS_data.Longitude] );
|
||||
for i = 1:numel(x)
|
||||
GPS_data(i).Position = gtsam.Point3(x(i), y(i), GPS_data(i).Altitude);
|
||||
end
|
||||
|
||||
% % Calculate GPS sigma in meters
|
||||
% [ xSig, ySig, ~ ] = deg2utm( [GPS_data.Latitude] + [GPS_data.PositionSigma], ...
|
||||
% [GPS_data.Longitude] + [GPS_data.PositionSigma]);
|
||||
% xSig = xSig - x;
|
||||
% ySig = ySig - y;
|
||||
|
||||
%% Start at time of first GPS measurement
|
||||
firstGPSPose = 1;
|
||||
% firstGPSPose = 1;
|
||||
|
||||
%% Get initial conditions for the estimated trajectory
|
||||
% currentPoseGlobal = Pose3(Rot3, GPS_data(firstGPSPose).Position); % initial pose is the reference frame (navigation frame)
|
||||
|
|
@ -82,7 +84,6 @@ isam = gtsam.ISAM2(isamParams);
|
|||
newFactors = NonlinearFactorGraph;
|
||||
newValues = Values;
|
||||
|
||||
|
||||
%% Main loop:
|
||||
% (1) we read the measurements
|
||||
% (2) we create the corresponding factors in the graph
|
||||
|
|
@ -90,12 +91,10 @@ newValues = Values;
|
|||
timestamps = sortrows( [ ...
|
||||
[VO_data.Time]' 1*ones(length([VO_data.Time]), 1); ...
|
||||
%[GPS_data.Time]' 2*ones(length([GPS_data.Time]), 1); ...
|
||||
%[IMU_data.Time]' 3*ones(length([IMU_data.Time]), 1); ...
|
||||
], 1); % this are the time-stamps at which we want to initialize a new node in the graph
|
||||
|
||||
timestamps = timestamps(15:end,:);
|
||||
|
||||
VOPoseKeys = [];
|
||||
timestamps = timestamps(15:end,:); % there seem to be issues with the initial IMU measurements
|
||||
VOPoseKeys = []; % here we store the keys of the poses involved in VO (between) factors
|
||||
|
||||
for measurementIndex = 1:length(timestamps)
|
||||
|
||||
|
|
@ -146,6 +145,7 @@ for measurementIndex = 1:length(timestamps)
|
|||
error('no IMU measurements in [t_previous, t]')
|
||||
end
|
||||
|
||||
% LC: sigma_init_b is wrong: this should be some uncertainty on bias evolution given in the IMU metadata
|
||||
newFactors.add(BetweenFactorConstantBias(currentBiasKey-1, currentBiasKey, imuBias.ConstantBias(zeros(3,1), zeros(3,1)), sigma_init_b));
|
||||
|
||||
%% Create GPS factor
|
||||
|
|
@ -172,19 +172,16 @@ for measurementIndex = 1:length(timestamps)
|
|||
newFactors = NonlinearFactorGraph;
|
||||
newValues = Values;
|
||||
|
||||
if rem(measurementIndex,20)==0
|
||||
if rem(measurementIndex,20)==0 % plot every 20 time steps
|
||||
cla;
|
||||
plot3DTrajectory(isam.calculateEstimate, 'g-');
|
||||
axis equal
|
||||
drawnow;
|
||||
end
|
||||
% =======================================================================
|
||||
|
||||
currentPoseGlobal = isam.calculateEstimate(currentPoseKey);
|
||||
currentVelocityGlobal = isam.calculateEstimate(currentVelKey);
|
||||
currentBias = isam.calculateEstimate(currentBiasKey);
|
||||
|
||||
end
|
||||
|
||||
|
||||
end % end main loop
|
||||
|
|
|
|||
Loading…
Reference in New Issue