Deep-fusion AI provides advanced 4D imaging radar solutions that enable comprehensive surrounding perception for autonomous systems. Their platform delivers real‑time 4D radar SLAM, integrating perceptive sensor fusion to create accurate, high‑resolution maps of dynamic environments.
Funding
Funding not disclosed
Founders
Product
Problem
Autonomous vehicles and robots require reliable perception of their surroundings in all weather conditions, but existing sensor suites often rely on cameras or LiDAR that can be degraded by rain, fog, or low light, leading to gaps in situational awareness and safety risks.
Solution
Deep-fusion AI offers a 4D imaging radar platform that generates high‑resolution, real‑time maps of dynamic environments. The system performs 4D radar simultaneous localization and mapping (SLAM) to track objects and construct detailed scene representations without dependence on ambient lighting. By fusing radar data with camera imagery, the platform delivers a comprehensive perception stack that maintains accuracy in adverse weather. The solution runs on automotive‑grade hardware, providing low‑latency outputs suitable for real‑time decision making in self‑driving cars and robotic platforms.
Target Audience
Primary customers are autonomous vehicle manufacturers, advanced driver‑assistance system (ADAS) providers, and robotics companies that need robust, all‑weather environmental perception.
Features
- 4D imaging radar sensor delivering high‑density point clouds with range, velocity, and elevation data
- Real‑time 4D radar SLAM algorithm for continuous mapping and localization
- Perceptive sensor fusion pipeline that combines radar with camera vision to enhance object classification and depth estimation
- All‑weather operation capability, maintaining performance in rain, fog, and low‑light conditions
- Automotive‑grade integration with standard vehicle networks and low power consumption