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`DetectObjectsEvent.java`\n  - `TrackedObjectsEvent.java`\n  - `PoseEvent.java`\n  - `TickBroadcast.java`\n  - `CrashedBroadcast.java`, `TerminatedBroadcast.java`\n\n- **`objects/`**  \n  Data representations of sensors, tracked objects, the robot pose, and statistics:\n  - `Camera.java`, `LiDarWorkerTracker.java`, `GPSIMU.java`\n  - `DetectedObject.java`, `TrackedObject.java`, `LandMark.java`\n  - `StampedCloudPoints.java`, `StampedDetectedObjects.java`\n  - `FusionSlam.java`, `Pose.java`, `CloudPoint.java`, `StatisticalFolder.java`\n  - `STATUS.java`, `LiDarDataBase.java`\n\n- **`services/`**  \n  Microservice implementations:\n  - `CameraService.java`\n  - `LiDarService.java`\n  - `FusionSlamService.java`\n\n---\n\n## ✨ Features\n- Fully event-driven concurrent design  \n- Global system timer using `TickBroadcast`  \n- Real-time pose-aware mapping with coordinate transformation  \n- Supports multiple sensors with different frequencies  \n- Fault detection \u0026 emergency shutdown using broadcast messages  \n- Generates a final JSON output containing runtime statistics, detected landmarks, and crash report (if applicable)  \n\n---\n\n## 🚀 How to Run\n\n### 1. Build\n```bash\nmvn clean compile\n```\n\n### 2. Run Tests\n```bash\nmvn test\n```\n\n### 3. Run Application\nTo run the simulation, provide the path to a valid configuration JSON file:\n```bash\nmvn exec:java -Dexec.mainClass=bgu.spl.mics.application.GurionRockRunner -Dexec.args=\"/path/to/configuration_file.json\"\n```\n\n---\n\n## 📄 Output Description\nGenerates an `output_file.json` in the same directory as the configuration file, containing:\n- Runtime statistics  \n- Final map (landmarks)  \n- Crash report (if applicable)\n\n---\n\n## 🧪 Testing\n```bash\nmvn test\n```\nIncludes unit tests for core components:\n- `MessageBusImpl` – Publish/subscribe mechanisms and future resolution\n- `FusionSlam` – Landmark transformation and pose estimation\n- Sensor services (`CameraService`, `LiDarService`) – Message handling and event generation\n\n---\n\n## 📁 Directory Structure\n```\nsrc/\n└── main/\n    └── java/\n        └── bgu/\n            └── spl/\n                └── mics/\n                    └── application/\n                        ├── messages/\n                        ├── objects/\n                        └── services/\n```\n\n---\n\n## 🔗 Example Configuration\nFor testing the system, several input sets are provided under the following folders:\n- `example_input/`\n- `example_input_2/`\n- `example_input_with_error/`\n\nEach folder contains a `configuration_file.json` and supporting sensor data (`camera_data.json`, `lidar_data.json`, `pose_data.json`, etc.).\n\n---\n\n## 📚 Course Information\n- **Course:** SPL225 – Systems Programming Lab  \n- **Institution:** Ben-Gurion University of the Negev  \n- **Year:** 2025  \n- **Environment:** Linux CS Lab, Docker-compatible  \n\n---\n\n## 🧑‍💻 Authors\n\n**Ben Kapon**  \nStudent at BGU  \n[LinkedIn](https://www.linkedin.com/in/ben-kapon1/)\n\n**Itay Shaul**  \nStudent at BGU  \n[LinkedIn](https://www.linkedin.com/in/itay-shaul/)\n\n---\n\n## 📝 Important Note\nThis project was designed and tested on a **Docker-compatible environment**.  \nEnsure file paths and JSON formats are valid when running in local or CI environments.\n\n\u003e This project demonstrates real-time sensor integration using advanced concurrent programming techniques in Java.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitayshaul111%2Fsmart-vacuum-robot-simulation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fitayshaul111%2Fsmart-vacuum-robot-simulation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitayshaul111%2Fsmart-vacuum-robot-simulation/lists"}