14 citations · 21 across the 12 of their papers we have counts for
13 papers
FORWARD: Dataset of a forwarder operating in rough terrain
Mikael Lundbäck, Erik Wallin, Carola Häggström +8
We present FORWARD, a high-resolution multimodal dataset of a cut-to-length forwarder operating in rough terrain on two harvest sites in the middle part of Sweden. The forwarder is…
A modular and extensible library for parameterized terrain generation
Erik Wallin
Simulation-driven development of intelligent machines benefits from artificial terrains with controllable, well-defined characteristics. However, most existing tools for terrain ge…
Synthesizing multi-log grasp poses in cluttered environments
Arvid Fälldin, Tommy Löfstedt, Tobias Semberg +2
Multi-object grasping is a challenging task. It is important for energy and cost-efficient operation of industrial crane manipulators, such as those used to collect tree logs from…
Multi-log grasping using reinforcement learning and virtual visual servoing
Erik Wallin, Viktor Wiberg, Martin Servin
We explore multi-log grasping using reinforcement learning and virtual visual servoing for automated forwarding in a simulated environment. Automation of forest processes is a majo…
Sim-to-real transfer of active suspension control using deep reinforcement learning
Viktor Wiberg, Erik Wallin, Arvid Fälldin +4
We explore sim-to-real transfer of deep reinforcement learning controllers for a heavy vehicle with active suspensions designed for traversing rough terrain. While related research…
Improving Open-Set Semi-Supervised Learning with Self-Supervision
Erik Wallin, Lennart Svensson, Fredrik Kahl +1
Open-set semi-supervised learning (OSSL) embodies a practical scenario within semi-supervised learning, wherein the unlabeled training set encompasses classes absent from the label…
DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision
Erik Wallin, Lennart Svensson, Fredrik Kahl +1
Following the success of supervised learning, semi-supervised learning (SSL) is now becoming increasingly popular. SSL is a family of methods, which in addition to a labeled traini…
Learning multiobjective rough terrain traversability
Erik Wallin, Viktor Wiberg, Folke Vesterlund +3
We present a method that uses high-resolution topography data of rough terrain, and ground vehicle simulation, to predict traversability. Traversability is expressed as three indep…
Control of rough terrain vehicles using deep reinforcement learning
Viktor Wiberg, Erik Wallin, Martin Servin +1
We explore the potential to control terrain vehicles using deep reinforcement in scenarios where human operators and traditional control methods are inadequate. This letter present…
Digital twins with distributed particle simulation for mine-to-mill material tracking
Martin Servin, Folke Vesterlund, Erik Wallin
Systems for transport and processing of granular media are challenging to analyse, operate and optimise. In the mining and mineral processing industries these systems are chains of…
Reinforcement Learning Control of a Forestry Crane Manipulator
Jennifer Andersson, Kenneth Bodin, Daniel Lindmark +2
Forestry machines are heavy vehicles performing complex manipulation tasks in unstructured production forest environments. Together with the complex dynamics of the on-board hydrau…
Data-driven model order reduction for granular media
Erik Wallin, Martin Servin
We investigate the use of reduced-order modelling to run discrete element simulations at higher speeds. Taking a data-driven approach, we run many offline simulations in advance an…
Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physics
A. Gonoskov, E. Wallin, A. Polovinkin +1
The validation of a theory is commonly based on appealing to clearly distinguishable and describable features in properly reduced experimental data, while the use of ab-initio simu…