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Artificial Perception technologies
The leading SLAM algorithms for all the embedded machines
What’s New
Kudan Announces Milestone Achieved on SLAM development; GigaPoint SLAM Map creation
January 31, 2019
Kudan Announces Milestone Achieved on SLAM development; GigaPoint SLAM Map creation
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Kudan has started offering a development partnership program on integration of visual-SLAM and LiDAR for visual-LiDAR-SLAM
December 27, 2018
Kudan has started offering a development partnership program on integration of visual-SLAM and LiDAR for visual-LiDAR-SLAM
How to evaluate SLAM accuracy
May 14, 2018
How to evaluate SLAM accuracy
KudanSLAM RGB-D SLAM
May 7, 2018
KudanSLAM RGB-D SLAM
List of articles
Product offerings
Visual-SLAM
SLAM for stereo/mono camera
SLAM for multiple camera
SLAM for 360 camera
Processor Optimisation
CPU SLAM (ARM, Intel)
GPU SLAM (CUDA, OpenCL)
DSP SLAM
Sensor Integration
SLAM with IMU
Depth SLAM (LiDAR, ToF)
SLAM with GPS
SLAM with mechanical odometory
Functional Algorithms
SLAM on saved maps (Asynchronous Localisation and Mapping)
Hybrid of SLAM and Visual Odometry
SLAM on ARkit/ARcore
CNN based SLAM
Connection Integration
Edge computing SLAM
Cloud SLAM system with distributed map generation
Contact us for more information
Features of KudanSLAM
Fully Proprietary Algorithms
Hybrid patch + descriptor approach leverages strengths of both
Efficient sparse representation with flexibility for post-processing densification.
Portable Libraries
Guaranteed portability across processor architectures (CPU, DSP, GPU)
Scalable algorithms optimized for major OS (Linux, Windows, Apple OS, Android)
Sensor Agnostic
Works with camera standalone or in combination with LiDAR, IMU, ToF, and Odometry
Interfaces with monocular, stereo and other cameras as well as with global + rolling shutters
Silicon + Software Solutions
50+ modular frameworks enable seamless integration with in-house solutions
Low-level and high/mid-level algorithms optimized at both silicon and software layers
Fast, Accurate and Efficient
Superior to other available solutions
Error of 1mm in 1m distance in synthetic environment
Find out more
Demo videos
Demos
More demos
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