Zedup provides a hardware‑agnostic LiDAR SLAM platform that converts 2D and 3D sensor data into real‑time, sub‑centimeter accurate maps and continuous 3D reconstructions. The solution enables autonomous robots, AGVs and drones to navigate precisely in factories, warehouses and outdoor sites, and integrates via standard SDKs and APIs for easy adoption.
Funding
Funding not disclosed
Founders
Product
Problem
Robotic systems and autonomous vehicles require reliable, high‑precision localization and mapping to operate safely in complex indoor and outdoor environments. Traditional mapping solutions often struggle with real‑time performance, accuracy, or adaptability to diverse sensor setups, limiting deployment in factories, warehouses, and outdoor sites.
Solution
Zedup delivers a LiDAR‑based SLAM platform that processes raw 2D and 3D sensor data into accurate, real‑time maps. The technology provides centimeter‑level localization for robots and AGVs, enabling autonomous navigation across varied environments. By generating detailed 3D reconstructions, the system supports both navigation and downstream tasks such as inspection or digital twin creation. Zedup’s solution is hardware‑agnostic and can be integrated into existing robotic stacks via standard APIs, offering a scalable foundation for next‑generation autonomous operations.
Target Audience
Primary customers are manufacturers, logistics providers, and robotics developers that need precise autonomous navigation for AGVs, mobile robots, and inspection drones in industrial or outdoor settings.
Features
- Real‑time 2D and 3D LiDAR SLAM with sub‑centimeter localization accuracy
- Continuous 3D environment rendering for mapping, visualization, and digital twin generation
- Support for diverse platforms, including indoor factories, warehouses, and outdoor spaces
- Seamless integration through SDKs and API bindings compatible with common robotics frameworks
- Optimized computational pipeline for low‑latency operation on edge hardware
- Robust handling of dynamic obstacles and complex geometries