Empowering the Future of
Driving the Future of Intelligent Mobility
In this rapidly evolving era, we are committed to long-term innovation, exploring safer, smarter, and more efficient robotic mobility.
With advances in intelligent perception, AI-driven decision-making, autonomous navigation, and predictive control, we aim to unlock the value of robots across industries, shaping the future of smart cities and intelligent logistics.
High-Precision Positioning, Orientation, and Environmental Perception Technologies
- Integrated positioning and orientation technology combining vision, LiDAR SLAM, and RTK;
- Dynamic position prediction and correction technology based on motion models;
- Hazard condition perception, early warning, and electronic fencing based on depth vision.
- High-refresh-rate, high-precision positioning algorithms for complex environments;
Motion Planning and Control Algorithms
- Spatial motion trajectory planning and control for multi-degree-of-freedom robots;
- Neural network modeling and training based on artificial intelligence;
- Robot motion workspace analysis and obstacle avoidance handling;
- Emergency handling mechanisms for abnormal states.
Deep Learning and Vision Algorithms
Neural network models can improve the accuracy and efficiency of recognizing objects such as traffic signs, road users, and obstacles, thereby enhancing the perception capabilities of autonomous driving systems regarding the surrounding environment and traffic conditions, and providing a basis for driving decisions, path planning, and obstacle avoidance.
The application of structured light point clouds and neural network models in end-effector vision for robotic arms enables object detection, positioning, and 3D reconstruction, providing more precise guidance for tasks such as grasping and assembly.
