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Discover a faster, easier way to build advanced AI robotics applications with the NVIDIA Isaac™ ROS collection of accelerated computing packages and AI models, bringing NVIDIA acceleration to ROS developers everywhere. Isaac ROS Visual SLAM provides a high-performance, best-in-class ROS 2 package for VSLAM (visual simultaneous localization and mapping). This package uses one or more stereo cameras and optionally an IMU to estimate odometry as an input to navigation. It is GPU-accelerated to provide real-time, low-latency results in a robotics application. VSLAM provides an additional odometry source for mobile robots (ground-based) and can be the primary odometry source for drones. VSLAM provides a method for visually estimating the position of a robot relative to its start position, known as VO (visual odometry). This is particularly useful in environments where GPS is not available (such as indoors) or intermittent.
Features
- SLAM (simultaneous localization and mapping) is built on top of VIO
- Documentation available
- VSLAM is a best-in-class package with the lowest translation and rotational error
- A Rich Collection of Models for Roboticists
- Modular, Flexible Packages
- High-Throughput Perception
- cuMotion for Robot Manipulation
- Multi-Camera Visual Inertial Odometry
Project Samples
