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Umeå universitet
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Huvudmenyn dold.
Personalbild Arvid Fälldin

Arvid Fälldin

Kontakt

E-post
arvid.falldin@umu.se
Telefon

Verksam som

Anknytning
Doktorand vid Institutionen för fysik Enhet: UMIT
Plats
MIT-huset, byggnad V, UMIT Research Lab, UMIT-lab Umeå universitet, 901 87 Umeå
World modeling for autonomous wheel loaders
Automation, MDPI 2024, Vol. 5, (3) : 259-281
Aoshima, Koji; Fälldin, Arvid; Wadbro, Eddie; et al.
Open data, models, and software for machine automation
IUFRO 2024: Detailed programme
Fälldin, Arvid; Häggström, Carola; Höök, Christian; et al.
Towards autonomous forwarding using deep learning and simulation
IUFRO 2024 - XXVI IUFRO World Congress, Stockholm, Sweden, June 23-29, 2024
Fälldin, Arvid; Lundbäck, Mikael; Servin, Martin; et al.
Learning forwarder trafficability from real and synthetic data
IUFRO 2024: Detailed programme
Lundbäck, Mikael; Fälldin, Arvid; Wallin, Erik; et al.
Sim-to-real transfer of active suspension control using deep reinforcement learning
Robotics and Autonomous Systems, Elsevier 2024, Vol. 179
Wiberg, Viktor; Wallin, Erik; Fälldin, Arvid; et al.
Learning by Digging: A Differentiable Prediction Model for an Autonomous Wheel Loader
Fälldin, Arvid
Data-driven models for predicting the outcome of autonomous wheel loader operations
Aoshima, Koji; Fälldin, Arvid; Wadbro, Eddie; et al.
Sim-to-real transfer of active suspension control using deep reinforcement learning
Wiberg, Viktor; Wallin, Erik; Fälldin, Arvid; et al.
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Forskargrupper

Gruppmedlem
Digital fysik

Forskningsprojekt

1 februari 2019 till 31 december 2026
Mistra Digital Forest