A Model-Predictive Motion Planner for the IARA autonomous car
Vinicius Cardoso, Josias Oliveira, Thomas Teixeira, Claudine Badue, Filipe Mutz, Thiago Oliveira-Santos, Lucas Veronese, Alberto F. De Souza
Abstract
We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a path from its current position to the desired destination. Using this path, the current position, a goal in the path and a map, IARA's MPMP is able to compute smooth trajectories from its current position to the goal in less than 50 ms. MPMP computes the poses of these trajectories so that they follow the path closely and, at the same time, are at a safe distance of occasional obstacles. Our experiments have shown that MPMP is able to compute trajectories that precisely follow a path produced by a Human driver (distance of 0.15 m in average) while smoothly driving IARA at speeds of up to 32.4 km/h (9 m/s).
BibTeX
@inproceedings{icra2017_amodelpredictive,
title = {A Model-Predictive Motion Planner for the IARA autonomous car},
author = {Vinicius Cardoso and Josias Oliveira and Thomas Teixeira and Claudine Badue and Filipe Mutz and Thiago Oliveira-Santos and Lucas Veronese and Alberto F. De Souza},
booktitle = {ICRA 2017},
year = {2017}
}