Spatial intelligence. Sorted.
Accurate, robust, easy to integrate spatial intelligence for OEMs with next generation products
Explore. Play. Move. Interact. Like never before.
Spend less, get to market faster, and scale more easily with Slamcore’s robust, accurate algorithms, offering 6 DoF pose tracking, 2.5D mapping and more.
Robust and accurate
Visual inertial SLAM provides robustness and accuracy for demanding applications.
Minimal CPU and memory usage
Real-time performance, with low CPU and memory requirements.
Optimised for embedded processors
Supports NVIDIA’s Jetson processors, plus Ambarella, Qualcomm and TI.
Commercial grade interfaces
Choose the right interface for your needs from ROS/ROS2, Python to C++.
Advanced sensor fusion
Supports additional sensor inputs, including wheel odometry, GPS and LIDAR.
Fast setup
Install with one click to be up and running in no time, and customize easily.
Your ambition. Our spatial intelligence.
FAQs
Slamcore’s SDK runs with your existing code, using a C++ API or ROS1 Melodic/ROS2 Foxy wrapper. Slamcore’s SDK and developer tools (visualizer, data recorder etc) also run in standalone mode through a command line or GUI.
Slamcore’s SDK provides a complete SLAM system, consisting of localization and mapping algorithms that fuse data from stereo cameras and IMU, and outputs pose and occupancy (2.5D map or occupancy grid) information. The SDK acts as an input to your navigation, obstacle avoidance or perception stack and can be easily integrated with your code using our C++ API or the ROS Navigation Stack.
Our standard SDK supports the Intel Realsense D435i and D455 cameras, together with wheel odometry. The SDK can be further extended to work with custom sensor solutions (stereo cameras, IMUs, GPS, Lidar etc).
The standard SDK currently supports the Nvidia Jetson Xavier NX, Xavier AGX and Nano, and x64 machines (Core i5, i7 or better). Our software can also be ported to custom compute hardware.
We currently support Ubuntu 18.04 LTS, Ubuntu 20.04 LTS and Jetpack.