The global embodied AI market has great potential, but traditional solutions face several challenges to widespread adoption.

Challenge: Delayed Deployment and High Costs.
Developers typically procure components like mobile bases, cameras, and robotic arms from fragmented channels. This low-volume purchasing leads to customization difficulties, as well as longer delivery and integration cycles.  With high single-unit costs and few ready-to-use solutions, scaling research and training becomes challenging.

JAKA Solution: 
JAKA Lumi uses JAKA's integrated drive-control joints, controllers, and robotic arms, all connected by a unified control system that enables setup in just 5 minutes. Its open APIs and modular design make it easy to expand and develop, significantly reducing hardware costs compared to traditional solutions. Currently available in China at an industry-leading low price, JAKA Lumi offers developers a highly cost-effective platform for robot training and R&D. International sales are pending certification.

Hardware: 6-DOF robotic arm with a 2 kg payload, ±160° waist rotation, ±180° neck rotation, 0-400 mm vertical workspace, and compatibility with various JAKA+ ecosystem end-effectors, including 3-finger and 5-finger dexterous hands and flexible soft grippers.
Perception:  A triple perception system featuring a chassis-mounted laser radar, 3D vision, and ultrasonic obstacle avoidance enables autonomous mapping and positioning. This ensures the JAKA Lumi platform can seamlessly navigate and avoid obstacles in high-traffic environments.

Challenge: Lack of Integrated Embodied Intelligence Systems.
After purchasing various hardware components, developers who wish to enable data collection, large model training, and deployment still need to independently call APIs, develop corresponding software and algorithms, and deal with high integration complexity, making development time-consuming and labor-intensive.

JAKA Solution:
Open Ecosystem: JAKA Lumi provides an efficient and comprehensive training toolchain that seamlessly integrates with large model platforms and supports mainstream simulation platforms such as MuJoCo and NVIDIA Isaac Sim.