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Merge pull request #6 from maxhilger/master
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correct residual size in soft constraint
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dan11003 authored Jan 3, 2024
2 parents 56eaeae + 99fadda commit f3f9f5a
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -152,7 +152,7 @@ The method generalizes across diverse environments without the need for returnin


### October 2023 - RadaRays
[RadaRays](https://arxiv.org/pdf/2310.03505.pdf) is a method for simulating radar data, released as a gazebo plugin. Mock et al. were able to simulate radar scans from a prior lidar map, and accurately estimate radar odometry in the MulRan dataset. The estimated trajectories closely resemble the odometry estimated from real radar data.
[RadaRays](https://arxiv.org/pdf/2310.03505.pdf) is a method for simulating radar data, released as a gazebo plugin. Mock et al. were able to simulate radar scans by raytracing within a lidar map, and accurately estimate radar odometry in the MulRan dataset. The estimated trajectories closely resemble the odometry estimated from real radar data. The [code](https://github.com/uos/radarays_ros) and a [gazebo radar plugin](https://github.com/uos/radarays_gazebo_plugins) for the project has been released.



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2 changes: 1 addition & 1 deletion include/cfear_radarodometry/n_scan_normal.h
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Expand Up @@ -279,7 +279,7 @@ class mahalanobisDistanceError {
}
static ceres::CostFunction* Create(
const Eigen::Vector3d& target_mean, const Eigen::Matrix3d& tar_sqrt_information, double alpha) {
return new ceres::AutoDiffCostFunction<mahalanobisDistanceError,1, 3>(new mahalanobisDistanceError (target_mean, tar_sqrt_information, alpha));
return new ceres::AutoDiffCostFunction<mahalanobisDistanceError,3, 3>(new mahalanobisDistanceError (target_mean, tar_sqrt_information, alpha));
}
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
private:
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2 changes: 1 addition & 1 deletion src/offline_odometry.cpp
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Expand Up @@ -271,7 +271,7 @@ void ReadOptions(const int argc, char**argv, OdometryKeyframeFuser::Parameters&
par.weight_intensity_ = vm["weight_intensity"].as<bool>();
par.compensate = !vm["disable_compensate"].as<bool>();
par.use_guess = true; //vm["soft_constraint"].as<bool>();
par.soft_constraint = false; // soft constraint is rarely useful, this is changed for testing of initi // vm["soft_constraint"].as<bool>();
par.soft_constraint = vm["soft_constraint"].as<bool>();
par.radar_ccw = vm["radar_ccw"].as<bool>();

}
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