SLAM software adds robotics OS integration, wheel odometry
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A new software release from SLAMcore for developers of robots and smart products with advanced location and mapping capability now features robotics operating system (ROS) integration, wheel odometry, and environment customization.
The company, specializing in spatial intelligence for autonomous location and mapping, said the new software release expands SLAMcore’s location/mapping capabilities (visual inertial SLAM) for developers of robots and consumer electronics products. Its software helps developers overcome the challenges commercial robots and consumer products experience in locating, mapping and perceiving the physical environment around them. It uses stereo cameras, inertial (IMU) and depth sensors to provide real-time location and mapping information.
The startup, which was a spinout from Imperial College in 2016, is focused on providing simultaneous localization 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.
This new release extends the value of SLAMcore’s spatial intelligence software with three new capabilities:
- 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 customization 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 software works ‘out-of-the-box’ with Intel RealSense sensors and x86/Nvidia Jetson compute to provide fast prototypes. The software can be further optimized for specific use-cases, custom hardware and additional sensors for use in a wide range of commercial robotics and consumer electronics products.
The company claims its spatial intelligence software significantly reduces development time and R&D investment required to solve complex SLAM challenges like real-time positioning and mapping. SLAMcore software is able to run locally in real-time on cost-effective compute devices. In addition, using visual SLAM enables better adaptability to dynamic environments which mixes robots, people and moving objects.
Owen Nicholson, founder and CEO of SLAMcore, said, “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.”
SLAMcore’s latest software release is available now. Licensing options include low-cost, per device monthly subscriptions and commercial use licenses for development and production.
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