In 2020, senior engineers Fredrik Tornéus and Kjell-Ove Mickelsson took on the challenge of completely redesigning the bulk flow in Narvik, Norway.
Automatic control of a wheel loader doing bucket filling can be solved using deep reinforcement learning. This was recently demonstrated in a simulator environment by a team from Algoryx, Epiroc, and Umeå University. The scientific paper was recently published in the journal Machines. In underground mines, specialized wheel loaders (LHD) are used for loading fragmented […]
Researchers and engineers at Algoryx and Umeå University present the first successful implementation of a reinforcement learning controlled forestry machine at IROS 2021.
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.
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 participates in accelerator program TINC is arranged by Nordic Innovation House in Silicon Valley, USA
Reports research conducted at Baidu Research where AGX Dynamics was used to set up a mechanical simulation of an excavator operating in terrain.
Today experiments with plants and processes are performed in virtual environments instead of expensive and time-consuming full-scale experiments.
Simulation software from Algoryx is already used by many ABB divsions and ABB has selected AGX Dynamics for integration in ABB RobotStudio.
Algoryx will present the paper Physics-based virtual environments for autonomous earthmoving and mining machinery.