AgiBot Deploys Real-World Reinforcement learning System in Manufacturing Pilot with longcheer Technology

SHANGHAI, Nov. 3, 2025 /PRNewswire/ — AgiBot, a robotics company specializing in embodied intelligence, announced a key milestone with the prosperous deployment of its real-World Reinforcement Learning (RW-RL) system on a pilot production line with Longcheer Technology.

The project marks the first request of real-world reinforcement learning in real industrial robotics, connecting advanced AI innovation with large-scale production and signaling a new phase in the evolution of intelligent automation for precision manufacturing.

Tackling the Core Challenges of Flexible manufacturing

Precision manufacturing lines have long relied on rigid automation systems that demand complex fixture design, extensive tuning, and costly reconfiguration. Even advanced “vision + force-control” solutions have struggled with parameter sensitivity, long deployment cycles, and maintenance complexity.

AgiBot’s Real-World Reinforcement Learning system addresses these long-standing pain points by enabling robots to learn and adapt directly on the factory floor. Within just tens of minutes, robots can acquire new skills, achieve stable deployment, and maintain long-term performance without degradation. During line changes or model transitions, only minimal hardware adjustments and standardized deployment steps are required, dramatically improving versatility while cutting time and cost.

Core Advantages of AgiBot’s Real-World Reinforcement Learning

* Rapid Deployment – Training time for new skills is reduced from weeks to minutes, achieving exponential gains in efficiency.
* High Adaptability – The system autonomously compensates for common variations such as part position and tolerance shifts, maintaining industrial-grade stability and a 100% task completion rate over extended operation.
* Flexible Reconfiguration – Task or product changes can be accommodated through fast retraining, without custom fixtures or tooling, overcoming the long-standing “rigid automation vs. variable demand” dilemma in consumer electronics manufacturing. The solution exhibits generality across workspace layouts and production lines, allowing quick transfer and reuse across diverse industrial scenarios. this milestone signifies a deep integration.