Drift

What is Drift?

Drift is an AI copilot for robotics simulations. It provides a CLI that helps users build, launch, and debug robotics simulation setups by describing goals in natural language, rather than assembling the full configuration manually.

The site positions Drift around orchestrating components commonly involved in robotics simulation workflows—ROS, a simulator, robot descriptions (URDF), launch configurations, and plugins—so you can go from an idea to a runnable simulation environment.

Key Features

• Complete simulation toolkit (ROS + simulator + plugins + OS orchestration): Drift is described as covering the elements needed to set up and run simulations, not just generating code snippets.
• Natural-language control: You can describe what you want in plain English (e.g., a mobile robot with sensors, or launching a manipulator in Gazebo), and Drift translates that into simulation setup details.
• Build and test from a single prompt: The product emphasizes creating a robot and world, launching it in simulation, and wiring up a control loop using one prompt.
• ROS and simulator-aware debugging: Drift tracks ROS and simulator states, identifies likely causes of issues, and applies fixes to help resolve problems.
• CLI workflow for prompts and execution: The CLI workflow shown includes initializing Drift, asking what to build, and executing when you press Enter—indicating an interactive prompt-driven flow.

How to Use Drift

1. Install Drift on Linux/Ubuntu using the provided command: curl -fsSL https://godrift.ai/install | bash.
2. Start the CLI by running drift in a terminal.
3. Describe your simulation task in natural language, then press Enter on an empty line to execute (the demo shows example prompts like creating a mobile robot with Lidar/camera, launching a manipulator in Gazebo, setting up pick-and-place, and debugging why a robot is not moving).
4. Use built-in examples and help by typing help in the CLI.

Use Cases

• Create a mobile robot simulation with sensors: Prompt Drift to “create a mobile robot with lidar and camera,” then use the generated setup to run the simulation.
• Launch a manipulator in Gazebo: Use a prompt such as “launch my manipulator in Gazebo” to generate the launch configuration and start the simulator with the manipulator.
• Set up a pick-and-place environment: Ask Drift to “setup a pick-and-place simulation” to assemble a usable simulation scenario.
• Debug motion problems in a robotics stack: If a robot “is not moving,” prompt Drift to diagnose issues by checking ROS and simulator states and applying fixes.
• Iterate on simulation and control wiring: Use a single prompt to build a robot/world, launch it, and connect the control loop for testing.

FAQ

• What platforms does Drift support? The page shows Linux/Ubuntu and provides an Ubuntu install command.

• How does Drift understand what I want to simulate? It uses natural-language input in the CLI and translates the description into simulation setup elements such as URDF files and launch configurations (as described on the site).

• Does Drift only generate code, or can it run simulations? The site describes Drift as providing a complete simulation toolkit and helping you set up and run simulations on the fly.

• What does “debugging” mean in Drift? Drift is described as tracking ROS and simulator states to find the root cause and fix issues.

• Are there upcoming features? Yes. The site lists “coming soon” items including starting worlds via templates and a robots gallery of prebuilt robot models.

Alternatives

• Manual ROS + simulator setup (compose launch files and URDFs): Instead of using an AI copilot, you would build the full simulation workflow yourself. This can provide fine-grained control but typically requires more setup effort.
• Simulation tooling that focuses on template environments: Tools that emphasize one-click worlds/templates can reduce environment setup time, but may not provide the same prompt-driven orchestration across ROS, URDF, and debugging described for Drift.
• Robot model libraries and editors: If your primary need is finding or customizing robot models, using prebuilt URDFs and model galleries may be faster than generating setups from prompts (though Drift’s stated scope includes orchestration and debugging).
• General-purpose coding assistants for robotics projects: Generic AI coding tools can help write ROS/launch configuration, but may not be specifically designed to track ROS/simulator state for robotics-aware debugging within the same workflow.