RobotRank

Benchmark your robot controllers

A cloud-based platform for evaluating quadruped and humanoid locomotion controllers. Test your algorithms across multiple simulation environments and compare results on our global leaderboard.

How It Works

Get started in three simple steps and see how your controller stacks up

Step 1

Connect your GitHub repo

Link your controller repository following our standard template structure

Step 2

Choose robot, simulation, and tasks

Select from multiple environments, robot models, and locomotion tasks

Step 3

Run benchmark & compare results

View detailed metrics and see how you rank against other controllers

Why RobotRank?

Comprehensive benchmarking tools designed for robotics researchers and developers

Cloud-hosted simulations

Run benchmarks without local computational resources

Multi-environment support

Test across PyBullet, MuJoCo, Isaac Sim, and more

Detailed KPIs

Analyze speed, energy efficiency, stability, and more

Anonymous submissions

Benchmark privately or share results publicly

Ready to benchmark your controller?

Join researchers and developers worldwide in advancing robotics locomotion