Robotics SLAM Map Visualizer

Real-time SLAM (Simultaneous Localization and Mapping) visualization | Multi-robot support | Advanced analytics & benchmarking

🗺️ Real-Time Mapping | 📍 Trajectory Tracking | 🔍 Landmark Detection | 📊 Performance Analytics

SLAM Controls & Settings

Active Robots: 1 | Loop Closures: 0 | Map Coverage: 0%

SLAM Map Visualization

📍 Trajectory Length: 0.00 m
🎯 Localization Error: 0.00 cm
⚡ SLAM FPS: 0 fps
🔄 Loop Closures: 0 detected
📊 Drift Estimate: 0.00 cm/m

Comparative Mode: Algorithm Benchmarking

No algorithm selected. Click any algorithm to select it.

How To Use Robotics SLAM Map Visualizer

1
📝 Step 1: Configure SLAM Parameters

Adjust map resolution, robot speed, and sensor noise to match your environment.

2
🗺️ Step 2: Start Mapping

Click "Start Mapping" to begin real-time SLAM visualization.

3
🤖 Step 3: Multi-Robot Support

Add multiple robots using the "Add Robot" button for collaborative mapping.

4
📊 Step 4: Benchmark Algorithms

Select an algorithm, then click "Compare Algorithms" to see performance metrics.

💡 Research Insights

• Loop closures indicate successful map correction – higher counts mean better long-term accuracy.
• Drift estimate >5cm/m suggests sensor calibration issues.
• Cartographer typically performs best for loop closure detection.

📊 Benchmarking Example
Environment: Indoor office (50m x 30m)
Results: Cartographer: 1.8 cm RMSE ✅

Frequently Asked Questions

What is SLAM in robotics?
SLAM (Simultaneous Localization and Mapping) is where a robot builds a map of an unknown environment while tracking its location within that map.
What algorithms are supported?
Gmapping (particle filter), Hector SLAM (scan matching), and Cartographer (graph optimization). Select any to benchmark.
What do loop closures indicate?
Loop closures occur when a robot recognizes a previously visited location, correcting accumulated drift.
Is my data secure?
Yes — all processing happens in your browser. No data is sent to any server.