"Robotics Toolbox" is one of open-source MATLAB^(R) Toolbox maintained by prof. Peter Corke, and another is Machine Version Toolbox. The toolbox provides many functions that are useful for the study and simulation of classical arm-type tobotics, for example such things as kinematics, dynamics, and trajectory generation. The Toolbox is based on a very general method of representing the kinematics and dynamics of serial-link manipulators.

These parameters are encapsulated in MATLAB(R) objects - robot objects can be created by the user for any serial-link manipulator and a number of examples are provided for well know robots such as the Puma 560 and the Stanford arm amongst others. The Toolbo also provides functions for manipulating and coverting between datatypes such as vectors, homogeneous transformations and unit-questernions which are necessary to represent 3-dimensional position and orientation.

Release:　　9.9

Release date:　　April 2014

Licence:　　LGPL

Toolbox home page: http://www.petercorke.com/robot

Discussion group: http://group.google.com.au/group/robotics-tool-box

This, the ninth release of the Toolbox, represents over fifteen years of development and a substantial level of maturity.  This version captures a large number of changes and extensions generated over the last two years which support my new book “Robotics, Vision & Control”.

The latest release of the Toolbox has been significantly extended to support mobile robots. For ground robots the Toolbox includes standard path planning algorithms (bug, distance transform, D*, PRM), kinodynamics planning (RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadcopter flying robot.

Advantages of the Toolbox are that:

• the code is quite mature and provides a point of comparison for other implementations of the same algorithms;
• the routines are generally written in a straightforward manner which allows for easy understanding, perhaps at the expense of computational efficiency. If you feel strongly about computational efficiency then you can always rewrite the function to be more efficient, compile the M-file using the MATLAB compiler, or create a MEX version;
• since source code is available there is a benefit for understanding and teaching.

For more detail information, please goto: http://www.petercorke.com/Robotics_Toolbox.html