The new release expands SLAMcore’s location/mapping capabilities (visual inertial SLAM) for developers of robots/consumer electronics products. The software helps developers overcome the challenges associated with locating, mapping and perceiving the physical environment around robots and consumer products. SLAMcore software uses stereo cameras, inertial (IMU) and depth sensors to provide real-time location and mapping information.
The company’s mission is to provide industry-leading location and mapping (SLAM) software which works on cost-effective sensors and processors - saving developers months of development time and enabling robust commercial robotics and autonomous consumer electronics products and this new release further extends the power, versatility and value of SLAMcore’s Spatial Intelligence software with three new capabilities:
- SLAMcore is providing deep integration between its Spatial Intelligence software and the Robot Operating System code (version 1.0). SLAMcore is already an active member and supporter of the ROS community, and with this new release developers using this widely adopted open source middleware will find it even easier to quickly solve SLAM challenges by integrating SLAMcore software directly with ROS based systems.
- Support for wheel odometry allows designers to feed additional motion data to the SLAMcore software for even more robust location estimates. Odometers provide data on wheel revolutions which can be converted to actual distance travelled by a robot. Combining this data stream with visual and inertial sensor data adds further robustness and accuracy to real-time position and mapping.
- Enabling high levels of customisation SLAMcore software can be tailored to perform well in a wide range of conditions: indoor and outdoor environments; low-light or highly variable light conditions; dynamic environments; warehouse, office, street and garden environments. Coping with different light conditions and types of environment is one of the most significant challenges for robots operating in real-world environments. Configuring SLAM algorithms to match the target environment conditions for a robot significantly improves both robustness and performance.
SLAMcore's software works ‘out-of-the-box’ with Intel RealSense sensors and x86/Nvidia Jetson compute to deliver prototypes quicker. The software can be further optimised for specific use-cases, custom hardware and additional sensors for use in a wide range of commercial robotics and consumer electronics products.
SLAMcore’s Spatial Intelligence software significantly reduces development time and R&D investment required to solve complex SLAM challenges like real-time positioning and mapping. The software is able to run locally in real-time on cost-effective compute devices. Furthermore using visual SLAM enables better adaptability to dynamic environments which mixes robots, people and moving objects.
Commenting Owen Nicholson, founder and CEO of SLAMcore, added: “Our role is to make it as easy as possible for developers to add robust, high performance SLAM capabilities to their products as quickly and cost effectively as possible. Working closely with ROS and its codebase, as well as delivering support for environment customization, and supporting new sensors like wheel odometry means that more developers can benefit from integrating our software into autonomous robots and consumer electronics.”
