Robotics Toolbox for MATLAB
| Developer(s) | Peter Corke |
|---|---|
| Stable release | 9.8
/ February 2, 2013 |
| Type | Robotics suite |
| License | LGPL |
| Website | http://www.petercorke.com/robot |
The Robotics Toolbox is mature software that supports research and teaching into arm-type and mobile robotics. This is free software but requires the proprietary MATLAB environment in order to execute.
The Toolbox provides many functions that are useful for the study and simulation of classical arm-type robotics, 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 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 Toolbox also provides functions for manipulating and converting between datatypes such as: vectors;homogeneous transformations; roll-pitch-yaw and Euler angles and unit-quaternions which are necessary to represent 3-dimensional position and orientation.
This ninth 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), kinodynamic planning (RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a Simulink model a of non-holonomic vehicle. The Toolbox also including a detailed Simulink model for a quadrotor flying robot.
Some characteristics of the Toolbox are:
- 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_file|MEX] version;
- since source code is available there is a benefit for understanding and teaching.
See also
References
- (PDF)
- Robotics, Vision & Control. Springer. 2011. ISBN 978-3-642-20143-1.