@rboticsdepth: MicroFactory is shifting industrial automation away from rigid, pre-programmed systems toward adaptive, small-footprint hardware. Founded by Igor Kulakov, the company develops compact, transparent robotic workstations that utilize human-in-the-loop training. Instead of writing code, operators physically guide the robotic arms to establish baseline trajectories, which the system’s AI refines for high-throughput execution. This video demonstrates the system executing a precise micro-assembly task: aligning and bonding tiny neodymium magnets. The sequence requires 27 autonomous actions driven by 23 human-recorded paths and 4 distinct AI models working in parallel. Assembling magnetic components is notoriously difficult in traditional robotics. Standard industrial arms rely on static coordinate systems. They cannot natively compensate for the dynamic, non-linear inverse-square forces introduced by a magnetic field, which often snap parts out of alignment and ruin calibration. The significance of this demonstration lies in the robot’s ability to handle external, unpredictable stimuli. MicroFactory’s proprietary AI models analyze force feedback and visual data in real-time. This allows the dual arms to dynamically adapt their grip and trajectory to counteract the chaotic magnetic pull, rather than failing when encountering real-world physical resistance. Developing automation that adapts to dynamic environmental variables is a critical step toward fully autonomous, flexible manufacturing lines. #robotics #engineering #futuretech

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Saturday 30 May 2026 14:54:20 GMT