Oskar Ljungqvist

According to our database, Oskar Ljungqvist authored at least 18 papers between 2016 and 2021.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2021

Improved Path Planning by Tightly Combining Lattice-Based Path Planning and Optimal Control.

Kristoffer Bergman, Oskar Ljungqvist, Daniel Axehill

IEEE Trans. Intell. Veh., 2021

2020

A Geometric Approach to On-road Motion Planning for Long and Multi-Body Heavy-Duty Vehicles.

Rui Oliveira, Oskar Ljungqvist, Pedro F. Lima, Jonas Mårtensson, Bo Wahlberg

CoRR, 2020

Estimation-aware model predictive path-following control for a general 2-trailer with a car-like tractor.

Oskar Ljungqvist, Daniel Axehill, Henrik Pettersson, Johan Löfberg

CoRR, 2020

Optimization-Based On-Road Path Planning for Articulated Vehicles.

Rui Oliveira, Oskar Ljungqvist, Pedro F. Lima, Bo Wahlberg

CoRR, 2020

A Geometric Approach to On-road Motion Planning for Long and Multi-Body Heavy-Duty Vehicles.

Rui Oliveira, Oskar Ljungqvist, Pedro F. Lima, Bo Wahlberg

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

On sensing-aware model predictive path-following control for a reversing general 2-trailer with a car-like tractor.

Oskar Ljungqvist, Daniel Axehill, Henrik Pettersson

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

An Optimization-Based Motion Planner for Autonomous Maneuvering of Marine Vessels in Complex Environments.

Kristoffer Bergman, Oskar Ljungqvist, Jonas Linder, Daniel Axehill

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019

A path planning and path-following control framework for a general 2-trailer with a car-like tractor.

Oskar Ljungqvist, Niclas Evestedt, Daniel Axehill, Marcello Cirillo, Henrik Pettersson

J. Field Robotics, 2019

Optimization-based motion planning for multi-steered articulated vehicles.

Oskar Ljungqvist, Kristoffer Bergman, Daniel Axehill

CoRR, 2019

A predictive path-following controller for multi-steered articulated vehicles.

Oskar Ljungqvist, Daniel Axehill

CoRR, 2019

Improved Optimization of Motion Primitives for Motion Planning in State Lattices.

Kristoffer Bergman, Oskar Ljungqvist, Daniel Axehill

Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019

2018

Receding-Horizon Lattice-Based Motion Planning with Dynamic Obstacle Avoidance.

Olov Andersson, Oskar Ljungqvist, Mattias Tiger, Daniel Axehill, Fredrik Heintz

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

On stability for state-lattice trajectory tracking control.

Oskar Ljungqvist, Daniel Axehill, Johan Löfberg

Proceedings of the 2018 Annual American Control Conference, 2018

Fuel-efficient Model Predictive Control for Heavy Duty Vehicle Platooning using Neural Networks.

Gustav Ling, Klas Lindsten, Oskar Ljungqvist, Johan Löfberg, Christoffer Norin, Christian A. Larsson

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Lattice-based motion planning for a general 2-trailer system.

Oskar Ljungqvist, Niclas Evestedt, Marcello Cirillo, Daniel Axehill, Olov Holmer

Proceedings of the IEEE Intelligent Vehicles Symposium, 2017

2016

Path tracking and stabilization for a reversing general 2-trailer configuration using a cascaded control approach.

Niclas Evestedt, Oskar Ljungqvist, Daniel Axehill

Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, 2016

Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT.

Niclas Evestedt, Oskar Ljungqvist, Daniel Axehill

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Path following control for a reversing general 2-trailer system.

Oskar Ljungqvist, Daniel Axehill, Anders Helmersson

Proceedings of the 55th IEEE Conference on Decision and Control, 2016