Are you a robotics expert working on mobile robots? Do you want your robots to generate 3D maps enriched with semantic information about surrounding objects? You’re in the right place! Explore our GitHub repository and discover COSE-MAP, an innovative Cooperative Semantic Mapping framework specifically designed for mobile robots, capable of associating objects with their intrinsic characteristics. This functionality is essential to enable robots to perform meaningful reasoning.
COSE-MAP leverages RGBD cameras to enable multiple robots to perform the following tasks:
- Object Detection and Recognition in Real 3D Environments: COSE-MAP allows robots to identify and recognize objects in the surrounding environment, supporting semantic mapping in various operational scenarios.
- Unified Database Storage: the framework enables the storage of collected information in a centralized database, optimizing data management—a critical component for effective semantic mapping.
- Dynamic Real-Time Map Generation: by retrieving and integrating stored data, COSE-MAP produces detailed maps during runtime, enhancing the efficiency of the semantic mapping process.
COSE-MAP is modular and flexible. It allows the integration of state-of-the-art object segmentation algorithms (such as YOLO and Mask-RCNN). Memory usage is optimized through selective storage of object instances and their positions, eliminating the need to retain the entire map.
COSE-MAP is released as open-source software, for the benefit of the global robotics community.
This is where it all started. The principles behind associating semantic information to objects in the environment for mobile robots using COSE-MAP originated here.
If you are considering adopting this new framework for semantic mapping in mobile robots, get in touch with us! We welcome your feedback and are ready to support you in integrating it into your codebase.
