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Model fitting/selection/evaluation using ROS message streams

Given a trajectory in form of a ROS articulation_msgs/TrackMsg message, the model_learner_msg node of the articulation_models package fits all available template models, selects the one with the smallest BIC (Bayesian Information Criterion), and publishes a ROS articulation_msgs/ModelMsg message. Note that this node can then be used in real-time, as it skips trajectory messages if necessary.

Model fitting/selection/evaluation using ROS service calls

Alternatively, you might want to run model fitting, selection and/or evaluation using ROS service calls. Corresponding services are provided by the model_learner_srv node and the model_learner_prior node in the articulation_models package.

Visualization of trajectories and models

Trajectories articulation_msgs/TrackMsg and models articulation_msgs/TrackMsg can be visualized in RVIZ easily by using the Track and Model Display. See articulation_rviz_plugin for how to set up RVIZ to properly display them.