The Mobile Robot Programming Toolkit

1. Purpose of this program

The main goal of the GUI program RawLogViewer is to allow users to quickly inspect, cut, or modify in many different ways a given Rawlog (datasets) gathered by a robot, with the idea of preparing it as the input to some other program, typically for localization (pf-localization) or mapping (kf-slam, rbpf-slam,...):

This application implements a simple Kalman Filter for solving the SLAM problem for generic 3D range-bearing sensors and a full 6D robot state space. This program is a front-end for the class mrpt::slam::CRangeBearingKFSLAM . All the parameters to the algorithm are passed through a configuration file in the command line. The filter processes actions and observations from a rawlog file and generates a number of files describing the evolution of the filter.

The application pf-localization implements a particle filter for localization (aka Markov Localization) of a mobile robot given odometry, a map of the environment and any number and combination of sensor observations such as a likelihood can be computed given the map. This generic implementation is possible through the generic design of metric maps in the MRPT C++ libraries.

Description

This GUI application is an extension to a similar Matlab program developed by J. Neira and J. D. Tardós (University of Zaragoza).

It allows extensive experimentation with data-association and the behavior of Kalman Filter-based 2D SLAM, in a didactic way.

1 Description

icp-slam is a front-end application to the MRPT C++ library class mrpt::slam::CMetricMapBuilderICP. This SLAM algorithm builds a map incrementally by aligning new range scans to either a point point or an occupancy grid map using the ICP algorithm. The ICP implementation itself can be found in the class mrpt::slam::CICP. See this tutorial describing the algorithm.

1. Description

rawlog-grabber is a command-line application which uses a generic sensor architecture to collect data from a variety of robotic sensors in real-time taking into account the different rates at which each sensor may work. All the data is time stamp-sorted and dumped into a Rawlog file. This program creates one thread for each sensor declared in the config file and then saves the timestamp-ordered observations to a rawlog file.

It is actually a front-end to the class mrpt::slam::CMetricMapBuilderRBPF. All the parameters to the algorithm are passed through a configuration file in the command line. The filter processes actions and observations from a rawlog file and optionally generates a number of files describing the evolution of the filter and the maps.

This GUI application displays a flat world where obstacles are described through an occupancy grid map and where the user can choose target locations for running reactive navigation simulations. The map can be changed to anyone supplied by the user, and all the options that determine the behavior of the navigation system can be as well modified by the user to experiment by changing values.

1. Overview

The application ro-localization implements a particle filter for localization (aka Markov Localization) for a mobile robot using odometry, a set of known fixed beacons. The sequence of robot observations is taken from a dataset file (rawlog): it is not intended for real-time operation on a robot, though the source code requires little modification to do so.

1. Description

This GUI program computes the intrinsic and distortion parameters of a monocular camera given a sequence of images of a checkerboard. The application is based on OpenCV code and supports several different sources of video: