33 citations · 50 across the 4 of their papers we have counts for
3 papers · 1 filter
PlanNetX: Learning an Efficient Neural Network Planner from MPC for Longitudinal Control
Jasper Hoffmann, Diego Fernandez, Julien Brosseit +5
Model predictive control (MPC) is a powerful, optimization-based approach for controlling dynamical systems. However, the computational complexity of online optimization can be pro…
Experience-Based Heuristic Search: Robust Motion Planning with Deep Q-Learning
Julian Bernhard, Robert Gieselmann, Klemens Esterle +1
Interaction-aware planning for autonomous driving requires an exploration of a combinatorial solution space when using conventional search- or optimization-based motion planners. W…
Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving
Tobias Kessler, Julian Bernhard, Martin Buechel +7
Although many research vehicle platforms for autonomous driving have been built in the past, hardware design, source code and lessons learned have not been made available for the n…