A simple, robust, and accurate 3D LiDAR SLAM system designed to just work.
KISS-SLAM is a 3D LiDAR SLAM system that provides simultaneous localization and mapping for robots using LiDAR data. It solves the problem of building accurate maps and estimating a robot's position in unknown environments with a focus on simplicity and robustness. The system is designed to work reliably across various scenarios with minimal configuration.
Robotics researchers, engineers, and developers working on autonomous systems, mobile robots, or drones that require LiDAR-based localization and mapping. It is also suitable for academic projects and industrial applications involving 3D perception.
Developers choose KISS-SLAM for its straightforward implementation, reliability, and accuracy without complex dependencies. Its open-source nature and active community allow for customization and continuous improvement, making it a practical alternative to more cumbersome SLAM systems.
A LiDAR SLAM system that just works
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Simple one-line pip install command makes setup trivial, as emphasized in the README with 'pip install kiss-slam'.
Configurable parameters for indoor and outdoor use ensure reliability across varied environments, with specific tuning suggestions provided.
Builds on proven foundations like KISS-ICP to deliver precise localization and mapping, backed by academic paper results.
Open-source and encourages contributions, with a contributors list and issue tracking for continuous improvement.
Lacks native support for multi-sensor fusion (e.g., IMU or cameras), which may restrict use in hybrid perception systems.
Relies primarily on README and command-line help, with no detailed tutorials or API guides beyond basic usage.
Active development beyond the paper may introduce breaking changes, as noted with the git tag for reproducibility.