L3 is a state-estimator for road-vehicles, using inexpensive readily-available LIDAR sensors. Orthogonally-mounted off-the-shelf SICK LIDAR scanners are used to estimate vehicle state using an information- theoretic optimisation. The L3 software runs in real-time, and has been tested over hundreds of kilometres (and many months) of data taken by the road-vehicles of the Mobile Robotics Group at Oxford.SHOW ALL
DESIGNNavigation Base Unit (NABU)
CODEJavascript Robotics Toolkit (JTK)
An example robotics toolkit, written in Javascsript to show the fundamentals of Simultaneous Localisation and Mapping (SLAM), and the principles of Markovian localisation. Example localisation methods in include that of the Extended Kalman Filter (EKF), and a Particle Filter (PF).
DESIGNA second-generation NDE inspection robot (eRobot)
CODEMOOS.Python
A set of bindings for the Mission Oriented Operating System (MOOS), maintained by the Oxford Mobile Robotics Group. The bindings use Boost.Python as the interface layer, allowing the code to make full use of MOOS improvements (as of MOOS V10, binary message transmission, compression, asynchronous send-receive).SOURCEFORGE.COM/PROJECTS/PYMOOS
from pymoos.XPCTcpSocket import *
from pymoos.CMOOSMsg import *
from pymoos.CMOOSCommObject import *
from pymoos.CMOOSCommPkt import *
...
m = MOOSApp()
m.SetOnConnectCallBack( m.DoRegistrations )
m.SetOnMailCallBack( m.MailCallback )
...
m.Run()