Abstract
An Evidential Sensor Model for Velodyne Scan Grids
For the development of driving assistance systems a
nd autonomous vehicles, a reference
perception equipment including navigable space dete
rmination and obstacles detection is a
key issue. The Velodyne sensor which provides high
definition and omnidirectional
information can be used for this purpose. Neverthel
ess, when scanning around the vehicle,
uncertainty necessarily arises due to unperceived a
reas and noisy measurements. This
paper proposes an inverse evidential model for the
Velodyne in order to exploit its
measurements in a 2D occupancy grid mapping framewo
rk. The evidential sensor model
interprets the data acquired from the Velodyne and
successively maps it to a Carthesian
evidential grid using a fusion process based on the
least commitment principle to
guarantee information integrity. Experimental resul
ts prove that this approach can handle
efficiently the uncertainties of the sensor and thu
s a highly reliable local reference map
near the vehicle can be built for every timestamped
perception system that needs
evaluation or calibration