7 citations · 11 across the 7 of their papers we have counts for
8 papers
Optimized and kinematically feasible multi-agent motion planning
Anja Hellander, Kristoffer Bergman, Daniel Axehill
Multi-agent motion planning (MAMP) is an important problem for autonomous systems with multiple agents. In this work we propose a two-step method for finding optimized and kinemati…
A COLREGs-Compliant Motion Planner for Autonomous Maneuvering of Marine Vessels in Complex Environments
Kristoffer Bergman, Oskar Ljungqvist, Jonas Linder +1
An enabling technology for future sea transports is safe and energy-efficient autonomous maritime navigation in narrow environments with other marine vessels present. This requires…
An Optimization-Based Motion Planner for Autonomous Maneuvering of Marine Vessels in Complex Environments
Kristoffer Bergman, Oskar Ljungqvist, Jonas Linder +1
The task of maneuvering ships in confined environments is a difficult task for a human operator. One major reason is due to the complex and slow dynamics of the ship which need to…
An Optimization-Based Receding Horizon Trajectory Planning Algorithm
Kristoffer Bergman, Oskar Ljungqvist, Torkel Glad +1
This paper presents an optimization-based receding horizon trajectory planning algorithm for dynamical systems operating in unstructured and cluttered environments. The proposed ap…
Optimization-based motion planning for multi-steered articulated vehicles
Oskar Ljungqvist, Kristoffer Bergman, Daniel Axehill
The task of maneuvering a multi-steered articulated vehicle in confined environments is difficult even for experienced drivers. In this work, we present an optimization-based traje…
Improved Path Planning by Tightly Combining Lattice-based Path Planning and Numerical Optimal Control
Kristoffer Bergman, Oskar Ljungqvist, Daniel Axehill
This paper presents a unified optimization-based path planning approach to efficiently compute locally optimal solutions to advanced path planning problems. The approach is motivat…
Improved Optimization of Motion Primitives for Motion Planning in State Lattices
Kristoffer Bergman, Oskar Ljungqvist, Daniel Axehill
In this paper, we propose a framework for generating motion primitives for lattice-based motion planners automatically. Given a family of systems, the user only needs to specify wh…
Combining Homotopy Methods and Numerical Optimal Control to Solve Motion Planning Problems
Kristoffer Bergman, Daniel Axehill
This paper presents a systematic approach for computing local solutions to motion planning problems in non-convex environments using numerical optimal control techniques. It extend…