The toolbox is branched from the source tree of "Little Ben".
Ben was one of only six vehicles to successfully complete the DARPA Urban Challenge on Nov. 3, 2007 in Victorville, CA.
Project Overview
The Sick LIDAR Matlab/C++ Toolbox is an open-source project released under a BSD Open-Source License that provides stable and easy-to-use C++ drivers for Sick LMS 2xx and Sick LD laser range finders. In addition to low-level drivers, the package also features an easy to use Mex interface, which allows the end-user to stream real-time range and reflectivity data directly into Matlab. This feature is especially attractive as it facilitates the rapid development of algorithms by exploiting the high-level functionality afforded by Matlab's vector-based operations. The toolbox is branched from the source code used by the Ben Franklin Racing Team during the DARPA Urban Challenge. Our entry — Little Ben — employed five Sick LMS 291 and LD-LRS LIDARs during the race, and was one of only six vehicles to successfully complete the 55 mile Urban Challenge Final Event.
Download the Toolbox
- Download the latest release of the Sick LIDAR Matlab/C++ Toolbox from here.
- Checkout the latest SVN snapshot anonymously via your command line as follows:
svn co https://sicktoolbox.svn.sourceforge.net/svnroot/sicktoolbox
Toolbox Features
- Multi-threaded Sick LMS 2xx C++ driver (RS-232/422)
- Data Acquisition: Acquire raw range and/or reflectivity returns, mean measured values, interlaced scans, and more...
- Configure: Set variant (field-of-view and scan resolution), measuring units, measuring mode, availability level, and more...
- Multi-threaded Sick LD C++ driver (TCP/IP via BSD Sockets)
- Data Acquisition: Acquire raw range and reflectivity values from multiple scan sectors
- Configure: Set Sick LD sector configuration including field-of-view and scan resolution
- Matlab Mex interface for acquiring data via both drivers
- Designed for use under Linux/Unix systems using GNU Autotools
- Plenty of C++ and Matlab example code
Screenshots
Sick LD LRS 1000 Cartesian plot. Generated over 360 degrees with 0.5 degree resolution.
Sick LD LRS 1000 streaming range and reflectivity values from multiple sectors.
Sick LMS 291-S14 streaming range and reflectivity values.
Sick LMS 291-S05 Cartesian plot. Generated over 180 degrees with 0.5 degree resolution.
Authors
The Sick LIDAR Matlab/C++ Toolbox was developed and is currently maintained by Jason Derenick and Thomas Miller at Lehigh University. Both are with the Vision, Assistive Devices, and Experimental Robotics (VADER) Laboratory in the Department of Computer Science and Engineering.
Acknowledgments
We'd like to thank our teammates on the Ben Franklin Racing Team who also contributed to the development of this toolbox, to include Aleksandr Kushleyev, Tully Foote, Jon Bohren, Alex Stewart, Brian Satterfield, Professor Daniel Lee and Professor John Spletzer. Additionally, we'd like to thank Douglas Paul for his work on the original Sick LMS driver.
This work was funded in part by Thales Communications, Inc., the Commonwealth of Pennsylvania, Department of Community and Economic Development, and by the National Science Foundation Partnerships for Innovation (PFI) Program under Grant No. 0650115. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Contact
Feature requests and bug reports should be submitted using the project's Sourceforge tracker system.
You can also send inquiries to: derenick (at) lehigh (dot) edu or spletzer (at) cse (dot) lehigh (dot) edu.
