Gradient based path optimization method for autonomous driving
Jennifer David, Rafael Valencia, Roland Philippsen, Pascal Bosshard, Karl Iagnemma
Abstract
This paper discusses the possibilities of extending and adapting the CHOMP motion planner [1] to work with a non-holonomic vehicle such as an autonomous truck with a single trailer. A detailed study has been done to find out the different ways of implementing these constraints on the motion planner. CHOMP, which is a successful motion planner for articulated robots produces very fast and collision-free trajectories. This nature is important for a local path adaptor in a multi-vehicle path planning for resolving path-conflicts in a very fast manner and hence, CHOMP was adapted. Secondly, this paper also details the experimental integration of the modified CHOMP with the sensor fusion and control system of an autonomous Volvo FH-16 truck and a set of experiments conducted on a real-time environment. Finally, additional simulations were also conducted to compare the performance of the different approaches developed to study the feasibility of employing CHOMP to autonomous vehicles.
BibTeX
@inproceedings{iros2017_gradientbasedpat,
title = {Gradient based path optimization method for autonomous driving},
author = {Jennifer David and Rafael Valencia and Roland Philippsen and Pascal Bosshard and Karl Iagnemma},
booktitle = {IROS 2017},
year = {2017}
}