The research paper “Continuous Control of an Underground Loader Using Deep Reinforcement Learning” was published in MDPI Machines in August 2021. We are happy tro announce that this paper has now been selected as an Editor’s Choice Article as noteworthy or likely to be of high interest to readers, and comprise key papers that highlight […]
Update April 13 2022: This paper was awarded Editors’ Choice Article as noteworthy or likely to be of high interest to readers, and comprise key papers that highlight some of the best current research published in Machines. Automatic control of a wheel loader doing bucket filling can be solved using deep reinforcement learning. This was […]
Researchers and engineers at Algoryx and Umeå University present the first successful implementation of a reinforcement learning controlled forestry machine at IROS 2021.
We used reinforcement learning to show that it’s possible to automate grasping of a randomly placed tree log with an AI-controlled forest machine.
Algoryx has used AGX Dynamics, Unity and ML-Agents for machine learning of an AI-controlled wheel loader.
AGX Dynamics for Unity has been verified by Unity Technologies to ensure it is optimized for the Unity real-time 3D development platform with a seamless user experience.
Algoryx is top ranked in the Swedish AI startup landscape, selected using criteria such as use of AI, scalability, access to and use of data, and the AI skills of their personnel.
Reports research conducted at Baidu Research where AGX Dynamics was used to set up a mechanical simulation of an excavator operating in terrain.
Algoryx has been awarded yet another MegaGrant from Epic Games for implementation of industry grade physics simulation in Unreal Engine.
Algoryx will present the paper Physics-based virtual environments for autonomous earthmoving and mining machinery.
Dr Martin Servin, senior scientist and co-founders of Algoryx, has been appointed as scientific advisor to Komatsu Limited.