The Comprehensive Ecosystem for ROS 2 Navigation & SLAM

🚀 Quick Start 📊 Features & Metrics 🌟 GitHub

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💡 More Than a Benchmark

BenchBot is not just an evaluation tool—it is a complete lifecycle ecosystem for professional ROS 2 development. From initial integration to final validation, it empowers teams to master their navigation stack.

The BenchBot Workflow

• 🧩 Integrate: Plug in any SLAM algorithm or Navigation stack with our modular plugin system.
• ⚙️ Optimize: Use the AI Auto-Tuner to automatically discover the perfect parameters for your robot.
• 📈 Monitor: Track evolution with industrial-grade metrics (ATE, SSIM, Coverage) over time.
• ✅ Validate: Ensure production readiness with automated CI/CD pipelines and reproducible Docker environments.

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⚡ Key Features

🤖 For Researchers🛠️ For Developers📦 For Enterprise🧠 AI Auto-Tuner

• Automated Metrics: Stop measuring by hand. Get ATE, RPE, SSD, and SSIM automatically.
• Comparative Analysis: Run 10 different SLAM configs and get a single PDF comparing them.
• Reproducibility: config_resolved.yaml guarantees your experiments are repeatable.

• CI/CD Integration: Run benchmarks in Headless mode on your Jenkins/GitHub Actions runners.
• Modular Architecture: Add your own SLAM algorithm or metric with a simple plugin system.
• Rich API: Full Python API for custom automations.

• O3DE Support: High-fidelity photorealistic simulations for client demos.
• Hardware-in-the-Loop: Calibrate sensor noise models to match your real robots.
• Dockerized: Deploy on any infrastructure without dependency hell.

• Bayesian Optimization: Uses Optuna to find the perfect SLAM parameters automatically.
• Hands-Free Tuning: Define a search range (e.g., particles: 30-100) and let the AI maximize accuracy.
• Objective-Driven: Minimizes ATE (Trajectory Error) to guarantee the best possible localization.

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📐 How It Works

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📚 Documentation Map

🚀 Getting Started

• Installation Guide: Setup dependencies and run your first benchmark.
• Simulators: Choose between low-poly (Gazebo) and photorealistic (O3DE).
• Quick Reference: Fast links for common tasks.

🧠 Deep Dive

• Metrics Explained: Understand ATE, SSIM, IoU, and more.
• Architecture: Learn how the orchestrator works under the hood.
• Auto-Tuner: Use AI to optimize your SLAM parameters.

🔧 Operations

• Troubleshooting: Solutions for common navigation and mapping issues.
• Headless Mode: Running benchmarks on servers without a GUI.
• Multi-SLAM: How to add and compare new algorithms.

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Maintained by the Guillaume Schneider • Version 1.0