From Mines to Power Batteries | Qingyan Precision's Second Vertical Embodied Intelligence Pilot Scenario Has Been Successfully Launched

On the opening day, Qingyan Precision "moved" the real production scenario of power batteries to the exhibition site, focusing on demonstrating typical tasks such as plugging and unplugging of automotive battery pack connectors, grabbing and assembling of components. This is the second vertical pilot scenario of embodied intelligence implemented by Qingyan Precision after the Yulin mining scenario, marking that its engineering capability has begun to realize cross-scenario replication from the mining industry to the automotive and new energy manufacturing fields. At present, this scenario has realized large-scale data collection at a leading power battery manufacturer, and has formed a complete closed loop covering real data collection, data governance, simulation verification, model training and real machine application.

| Qingyan Precision has realized large-scale implementation of real scenarios at leading power battery plants

01 Focus on power batteries to restore real industrial tasks

The site is set up with three major sections: power battery scenario implementation demonstration, virtual simulation interactive experience, cross-scenario reproduction and real-scenario practical training. Visitors can observe the robots performing connector plugging and unplugging, component grabbing and assembly at close range, and also understand how real tasks are digitally reproduced through virtual simulation, as well as how the robot's operation capability gradually evolves from data collection and virtual training to real machine execution.

This demonstration is not a single robot motion demonstration, but a concentrated presentation of the complete capability chain required for embodied intelligence to enter real industrial scenarios.

02 The engineering closed loop from data to real machine

In the power battery scenario, Qingyan Precision focuses on demonstrating capabilities in five aspects:

The first is the capability of data collection and processing in real scenarios. Focusing on tasks such as battery pack connector plugging and unplugging, component grabbing and assembly, it collects data of the operation process, scenario environment and object status, and completes data cleaning, sorting and post-processing.

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The second is the capability of digital twin and scenario reproduction. It maps real equipment, processes and operation objects to the virtual environment, reproduces typical power battery tasks in the digital space, and provides a basis for robot training and verification.

The third is the capability of simulation deduction and virtual-real synchronous verification. Different task states and operation conditions are expanded through virtual simulation, and the training results in the virtual environment are compared with the real machine operation to continuously identify and narrow the gap between virtual and reality.

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The fourth is the capability of dexterous operation and motion mapping. Through operation data collection and synchronous mapping with the three-finger dexterous hand, the robot is promoted to complete continuous motions such as approaching, alignment, grabbing, plugging/unplugging and assembly.

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The fifth is the capability of pilot verification and on-site takeover. Before entering the actual production environment, the data, models, equipment and task processes are repeatedly trained and evaluated, then the verified capabilities are connected to the real machine, and continuous iteration is carried out according to the execution results.

03 From the first stop to the second stop, verifying the cross-scenario replication capability

Previously, Qingyan Precision's first vertical pilot scenario of embodied intelligence has been implemented in the Yulin mining scenario, forming an engineering closed loop from real data collection, data governance, simulation training, pilot verification to on-site deployment.

The implementation of this power battery scenario is another verification of Qingyan Precision's engineering capability. From mines to power batteries, the operating environment, operation objects and specific processes have changed, but the underlying implementation path remains consistent: select task points from real industrial demands, complete scenario and equipment calibration, collect real operation data, carry out data governance and simulation verification, then connect the trained and evaluated capabilities to the real machine, and continue to iterate through on-site feedback.

The "cross-scenario replication" emphasized by Qingyan Precision does not mean directly applying the same model to different industries without adaptation, but reusing the formed data tools, simulation platforms, pilot processes and engineering experience, and then completing targeted adaptation and verification according to new scenarios and tasks.

04 Continuously build the industrial embodied intelligence infrastructure

Incubated by Tsinghua University, Qingyan Precision is a physical AI enterprise oriented to the large-scale implementation of vertical scenarios of embodied intelligence. Relying on eight years of data accumulation and engineering practice in the fields of autonomous driving, new energy and industry, the company has built a trinity core capability of "embodied data engine, scenario simulation and verification toolchain, and vertical world model", which connects the whole link of real data collection, data governance, synthetic data, simulation deduction, verification and evaluation, and model iteration.

At present, Qingyan Precision's solutions have been implemented in more than 30 countries around the world, covering new energy vehicles, power batteries, energy storage, core components, mines, electric power and other fields, providing in-depth services for more than 100 leading enterprises.

From the first mining scenario to the second power battery scenario, Qingyan Precision is continuously verifying the engineering implementation and cross-scenario replication capability of embodied intelligence through one real vertical scenario after another, promoting robots to move from algorithms and demonstrations to real industrial tasks. In the future, the company will continue to improve the industrial embodied intelligence infrastructure, build a physical AI system of "one set of base, one model, hundreds of vertical scenario applications", and accelerate the large-scale and industrialized implementation of embodied intelligence in more industrial scenarios.