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 […]
Algoryx participated at Unity AI Summit 2021 with a much-appreciated presentation on how AGX Dynamics for Unity can be used to develop AI-controlled autonomous machines.
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 […]
Soon, European factories will be designed and operated by artificial intelligence. The AIToC project develops Artificial Intelligence supported Tool Chains in Manufacturing Engineering to make this possible.
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.
AGX Dynamics is well known for its fast and stable direct solver. In 2.19 we have improved the performance.