Are you a roboticist working on mobile robots? Do you want your robots to collect 3D maps with semantic information about the surrounding objects? Look no further! Check out our GitHub repository and discover COSE-MAP, an innovative Cooperative Semantic Mapping framework designed specifically for mobile robots to perform an association between the objects and their intrinsic features. This is essential to allow robots to reason meaningfully.
COSE-MAP leverages RGBD cameras to enable multiple robots to achieve the following tasks:
- Object Detection and Recognition in real 3D Environments: COSE-MAP empowers robots to identify and recognize objects within their surroundings, aiding in the process of semantic mapping for mobile robots in various scenarios.
- Unified Database Storage: the framework allows robots to store information in a unified database for efficient data handling, crucial for semantic mapping in mobile robot operations.
- Dynamic Map Creation at Runtime: by retrieving and combining information from the database, COSE-MAP generates detailed maps at runtime, optimizing the process which is vital for semantic mapping for robots.
COSE-MAP is modular and flexible. You can use state-of-the-art instance segmentation algorithms (such as YOLO and Mask-RCNN). Memory usage is optimized by selectively storing instances and their locations, avoiding the need to memorize the entire map.
COSE-MAP is released as open source, benefiting the global robotics community.
Here is where it all started from. The principles behind associating information to objects in the environment for mobile robots with COSE-MAP originated here.
If you’re considering adopting this novel framework for semantic mapping for mobile robots, let us know! We welcome your feedback and are here to assist with integration into your code.
