TY  - JOUR
AU  - Miguel Oliveira
AU  - Victor Santos
AU  - Angel Sappa
AU  - P. Dias
AU  - A. Moreira
PY  - 2016//
TI  - Incremental Scenario Representations for Autonomous Driving using Geometric Polygonal Primitives
T2  - RAS
JO  - Robotics and Autonomous Systems
SP  - 312
EP  - 325
VL  - 83
PB  - Elsevier B.V.
KW  - Incremental scene reconstruction
KW  - Point clouds
KW  - Autonomous vehicles
KW  - Polygonal primitives
N2  - When an autonomous vehicle is traveling through some scenario it receives a continuous stream of sensor data. This sensor data arrives in an asynchronous fashion and often contains overlapping or redundant information. Thus, it is not trivial how a representation of the environment observed by the vehicle can be created and updated over time. This paper presents a novel methodology to compute an incremental 3D representation of a scenario from 3D range measurements. We propose to use macro scale polygonal primitives to model the scenario. This means that the representation of the scene is given as a list of large scale polygons that describe the geometric structure of the environment. Furthermore, we propose mechanisms designed to update the geometric polygonal primitives over time whenever fresh sensor data is collected. Results show that the approach is capable of producing accurate descriptions of the scene, and that it is computationally very efficient when compared to other reconstruction techniques.
L1  - http://refbase.cvc.uab.es/files/OSS2016a.pdf
UR  - http://dx.doi.org/10.1016/j.robot.2016.05.011
N1  - ADAS; 600.086,  600.076
ID  - Miguel Oliveira2016
ER  -