ROSscavengers

ROSscavengers is an open-source robotics software framework designed to enable autonomous scavenging tasks using the Robot Operating System (ROS). It targets scenarios in which a robot must locate, retrieve, and reclaim scattered objects in structured indoor environments, such as warehouses, labs, or post-disaster settings, while emphasizing safety and reliability. The project prioritizes modularity, reusability, and interoperability with the broader ROS ecosystem.

The architecture of ROSscavengers is modular and plugin-based. Core components include perception modules (sensor fusion, object recognition), localization and mapping (SLAM, occupancy grids), task planning and decision making (behavior trees or finite-state machines), motion planning and control, and manipulation interfaces for grippers or end effectors. A common data exchange layer, built on ROS topics, services, and actions, supports seamless integration of separate perception, planning, and manipulation modules. The framework includes simulation tooling and hardware abstraction to ease testing in Gazebo or RViz before real-world deployment.

Developed by a diverse community of researchers and educators, ROSscavengers is distributed under an open-source license and hosted on public repositories. It provides documentation, example missions, and testing workflows to help teams validate algorithms for scavenging tasks while encouraging contributions and peer review. Typical use cases span research prototyping, educational demonstrations, and practical reclamation tasks in controlled environments.

In summary, ROSscavengers offers a ROS-based, modular platform for autonomous scavenging that integrates perception, localization, planning, and manipulation to reclaim scattered resources in safe, repeatable experiments.