function [values, measurements] = covarianceAnalysisCreateTrajectory( options, metadata ) % Create a trajectory for running covariance analysis scripts. % 'options' contains fields for including various factor types and setting trajectory length % 'metadata' is a storage variable for miscellaneous factor-specific values % Authors: Luca Carlone, David Jensen % Date: 2014/04/16 import gtsam.*; values = Values; warning('fake angles! TODO: use constructor from roll-pitch-yaw when using real data - currently using identity rotation') if options.useRealData == 1 %% Create a ground truth trajectory from Real data (if available) fprintf('\nUsing real data as ground truth\n'); gtScenario = load('truth_scen2.mat', 'Time', 'Lat', 'Lon', 'Alt', 'Roll', 'Pitch', 'Heading',... 'VEast', 'VNorth', 'VUp'); % Limit the trajectory length options.trajectoryLength = min([length(gtScenario.Lat) options.trajectoryLength]); fprintf('Scenario Ind: '); for i=0:options.trajectoryLength scenarioInd = options.subsampleStep * i + 1; fprintf('%d, ', scenarioInd); if (mod(i,20) == 0) fprintf('\n'); end %% Generate the current pose currentPoseKey = symbol('x', i); currentPose = imuSimulator.getPoseFromGtScenario(gtScenario,scenarioInd); % add to values values.insert(currentPoseKey, currentPose); %% gt Between measurements if options.includeBetweenFactors == 1 && i > 0 prevPose = values.at(currentPoseKey - 1); deltaPose = prevPose.between(currentPose); measurements(i).deltaVector = Pose3.Logmap(deltaPose); end %% gt IMU measurements if options.includeIMUFactors == 1 currentVelKey = symbol('v', i); currentBiasKey = symbol('b', i); deltaT = 0.01; % amount of time between IMU measurements if i == 0 currentVel = [0 0 0]'; else % integrate & store intermediate measurements for j=1:options.subsampleStep % we integrate all the intermediate measurements previousScenarioInd = options.subsampleStep * (i-1) + 1; scenarioIndIMU1 = previousScenarioInd+j-1; scenarioIndIMU2 = previousScenarioInd+j; IMUPose1 = imuSimulator.getPoseFromGtScenario(gtScenario,scenarioIndIMU1); IMUPose2 = imuSimulator.getPoseFromGtScenario(gtScenario,scenarioIndIMU2); IMURot2 = IMUPose2.rotation.matrix; IMUdeltaPose = IMUPose1.between(IMUPose2); IMUdeltaPoseVector = Pose3.Logmap(IMUdeltaPose); IMUdeltaRotVector = IMUdeltaPoseVector(1:3); IMUdeltaPositionVector = IMUPose2.translation.vector - IMUPose1.translation.vector; % translation in absolute frame measurements(i).imu(j).deltaT = deltaT; % gyro rate: Logmap(R_i' * R_i+1) / deltaT measurements(i).imu(j).gyro = IMUdeltaRotVector./deltaT; % deltaPij += deltaVij * deltaT + 0.5 * deltaRij.matrix() * biasHat.correctAccelerometer(measuredAcc) * deltaT*deltaT; % acc = (deltaPosition - initialVel * dT) * (2/dt^2) measurements(i).imu(j).accel = IMURot2' * (IMUdeltaPositionVector - currentVel.*deltaT).*(2/(deltaT*deltaT)); % Update velocity currentVel = currentVel + IMURot2 * measurements(i).imu(j).accel * deltaT; end end % Add Values: velocity and bias values.insert(currentVelKey, LieVector(currentVel)); values.insert(currentBiasKey, metadata.imu.zeroBias); end end fprintf('\n'); else error('Please use RealData') %% Create a random trajectory as ground truth currentPose = Pose3; % initial pose % initial pose unsmooth_DP = 0.5; % controls smoothness on translation norm unsmooth_DR = 0.1; % controls smoothness on rotation norm fprintf('\nCreating a random ground truth trajectory\n'); currentPoseKey = symbol('x', 0); values.insert(currentPoseKey, currentPose); for i=1:options.trajectoryLength % Update the pose key currentPoseKey = symbol('x', i); % Generate the new measurements gtDeltaPosition = unsmooth_DP*randn(3,1) + [20;0;0]; % create random vector with mean = [20 0 0] gtDeltaRotation = unsmooth_DR*randn(3,1) + [0;0;0]; % create random rotation with mean [0 0 0] measurements.deltaMatrix(i,:) = [gtDeltaRotation; gtDeltaPosition]; % Create the next pose deltaPose = Pose3.Expmap(measurements.deltaMatrix(i,:)'); currentPose = currentPose.compose(deltaPose); % Add the current pose as a value values.insert(currentPoseKey, currentPose); end % end of random trajectory creation end % end of else end % end of function