| Cstomp_moveit::utils::kinematics::IKSolver | Wrapper around an IK solver implementation |
| Cstomp_moveit::utils::MultivariateGaussian | Generates samples from a multivariate gaussian distribution |
| ▼Cplanning_interface::PlannerManager [external] | |
| Cstomp_moveit::StompPlannerManager | The PlannerManager implementation that loads STOMP into moveit |
| ▼Cplanning_interface::PlanningContext [external] | |
| Cstomp_moveit::StompPlanner | The PlanningContext specialization that wraps the STOMP algorithm |
| ▼Cplanning_request_adapter::PlanningRequestAdapter [external] | |
| Cstomp_moveit::StompSmoothingAdapter | |
| CPluginData | Packs plugin information into a single struct |
| Cstomp_moveit::utils::polynomial::PolyFitRequest | The Polynomial Fit request data |
| Cstomp_moveit::utils::polynomial::PolyFitResults | The Polynomial Fit results data |
| ▼Cstomp_moveit::cost_functions::StompCostFunction | Assigns a cost value to each robot state by evaluating the minimum distance between the robot and the nearest obstacle |
| Cstomp_moveit::cost_functions::CollisionCheck | Assigns a cost value to each robot state by evaluating if the robot is in collision |
| Cstomp_moveit::cost_functions::ObstacleDistanceGradient | |
| Cstomp_moveit::StompNoiseGenerator | Interface class for plugins that apply random noise to the trajectory in order to explore the workspace |
| ▼Cstomp_moveit::noise_generators::StompNoiseGenerator | |
| Cstomp_moveit::noise_generators::NormalDistributionSampling | Uses a normal distribution to apply noise onto the trajectory |
| ▼Cstomp_moveit::noisy_filters::StompNoisyFilter | Interface class for filtering noisy trajectories |
| Cstomp_moveit::noisy_filters::JointLimits | Checks that the joint values are within the limits as defined in the urdf file. It modifies the values of those joints that exceed the limits |
| Cstomp_moveit::noisy_filters::MultiTrajectoryVisualization | Publishes rviz markers to visualize the noisy trajectories |
| ▼Cstomp_moveit::update_filters::StompUpdateFilter | Interface class which applies filtering methods to the update parameters before it is added onto the optimized trajectory |
| Cstomp_moveit::update_filters::ControlCostProjection | |
| Cstomp_moveit::update_filters::PolynomialSmoother | This is a constrained polynomial trajectory smoother |
| Cstomp_moveit::update_filters::TrajectoryVisualization | Publishes rviz markers to visualize the optimized trajectory |
| Cstomp_moveit::update_filters::UpdateLogger | Saves the update values into a file for post analysis. The file is compatible with the python numpy library and can be loaded into a numpy array by running. 'numpy.loadtxt(file_name)' |
| ▼Cstomp_core::Task [external] | |
| Cstomp_moveit::StompOptimizationTask | Loads and manages the STOMP plugins during the planning process |
| Cstomp_moveit::update_filters | Uses a Control Cost Matrix projection in order to smooth out the trajectory. The matrix is built using a numerical derivative method |