aiofranka 0.3.0

A Python package for Franka robot control using asyncio.

aiofranka

aiofranka is an asyncio-based Python library for controlling Franka Emika robots. It provides a high-level, asynchronous interface that combines pylibfranka for official low-level control interface (1kHz torque control), MuJoCo for kinematics/dynamics computation, Ruckig for smooth trajectory generation.

The library is designed for research applications requiring precise, real-time control with minimal latency and maximum flexibility.

Installation

Make sure you can access Franka Desk GUI from your machine's browser by typing in the robot's IP (e.g. 172.16.0.2). Then, install:

pip install aiofranka

Or for development:

git clone https://github.com/Improbable-AI/aiofranka.git
cd aiofranka
pip install -e .

Quick Start

There are two ways to use aiofranka:

Option A: Server mode

Run the 1kHz control loop in a subprocess. Your scripts use a simple sync API — no async/await needed.

• No async/await — plain Python scripts, easy to integrate with existing codebases
• Process-isolated — heavy computation (policy inference, camera processing) can't starve the 1kHz loop
• Automatic lifecycle — server subprocess starts with your script and stops when it exits

import numpy as np
import aiofranka
from aiofranka import FrankaRemoteController

# 1. Unlock the robot (opens brakes + activates FCI)
aiofranka.unlock()

# 2. Create controller and start server subprocess
controller = FrankaRemoteController()
controller.start()

# 3. Use the robot
controller.move([0, 0, 0.0, -1.57079, 0, 1.57079, -0.7853])

controller.switch("impedance")
controller.kp = np.ones(7) * 80.0
controller.kd = np.ones(7) * 4.0
controller.set_freq(50)

for cnt in range(100):
    state = controller.state
    delta = np.sin(cnt / 50.0 * np.pi) * 0.1
    controller.set("q_desired", delta + controller.initial_qpos)

# 4. Stop server and lock robot
controller.stop()
aiofranka.lock()

The server subprocess terminates automatically when your script exits (Ctrl+C, crash, etc.), so it won't leave orphaned processes. controller.start() checks that the robot is unlocked and FCI is active before launching — if not, it prints a status summary and exits cleanly.

Option B: Async mode

Run the 1kHz control loop in-process using asyncio — everything in a single script.

• Single script — no separate server process, simpler deployment
• Direct access — no IPC overhead, full control over the event loop
• Requires async discipline — any blocking call >1ms after controller.start() will cause communication_constraints_violation (see Async Mode Guide)

import asyncio
import numpy as np
from aiofranka import RobotInterface, FrankaController

async def main():
    robot = RobotInterface("172.16.0.2")
    controller = FrankaController(robot)

    await controller.start()
    await controller.move([0, 0, 0.0, -1.57079, 0, 1.57079, -0.7853])

    controller.switch("impedance")
    controller.kp = np.ones(7) * 80.0
    controller.kd = np.ones(7) * 4.0
    controller.set_freq(50)

    for cnt in range(100):
        delta = np.sin(cnt / 50.0 * np.pi) * 0.1
        init = controller.initial_qpos
        await controller.set("q_desired", delta + init)

    await controller.stop()

if __name__ == "__main__":
    asyncio.run(main())

CLI Reference

The CLI handles robot setup and diagnostics. The server itself is started from Python (see Quick Start above).

aiofranka unlock   [--ip IP]              Unlock joints + activate FCI
aiofranka lock     [--ip IP]              Lock joints + deactivate FCI
aiofranka gravcomp [--ip IP] [--damping]  Gravity compensation (freedrive)
aiofranka status   [--ip IP]              Show robot & server status
aiofranka stop     [--ip IP]              Stop a running server
aiofranka mode     [--ip IP] [--set MODE] View/change operating mode
aiofranka config   [--ip IP] [--mass M]   View/set end-effector config
aiofranka selftest [--ip IP] [--force]    Run safety self-tests
aiofranka log      [-n LINES] [-f]        View server logs

unlock / lock

Unlock opens the brakes and activates FCI so the robot is ready for torque control. Lock does the reverse. Credentials are prompted on first use and saved to ~/.aiofranka/config.json.

# Unlock before running your script
aiofranka unlock

# Lock when you're done
aiofranka lock

You can also do this from Python:

import aiofranka
aiofranka.unlock()   # opens brakes + activates FCI
# ... run your control script ...
aiofranka.lock()     # closes brakes + deactivates FCI

gravcomp

Runs gravity compensation mode in the foreground. The robot is freely movable by hand. Press Ctrl+C to stop and lock.

aiofranka gravcomp                  # default: zero damping
aiofranka gravcomp --damping 2.0    # add velocity damping

status

Shows robot state (joints locked/unlocked, FCI active/inactive, control token, self-test status, end-effector configuration) and server status if running.

aiofranka status

stop

Sends a shutdown signal to a running server process. The server deactivates FCI, locks joints, and releases the control token.

aiofranka stop

mode

View or change the operating mode. Execution is needed for FCI control. Programming enables freedrive via the pilot interface button near the end-effector.

aiofranka mode                  # view current mode
aiofranka mode --set Execution  # switch to FCI mode

config

View or set the end-effector configuration (mass, center of mass, inertia, flange-to-EE transform). Changes are applied via the Franka Desk API.

aiofranka config                                # view current config
aiofranka config --mass 0.5 --com 0,0,0.03      # set mass + CoM
aiofranka config --translation 0,0,0.1           # set flange-to-EE offset

selftest

Run the robot's safety self-tests. The robot will lock joints during the test.

aiofranka selftest          # run if due
aiofranka selftest --force  # run even if not due

log

View recent server log entries from ~/.aiofranka/server.log.

aiofranka log              # last 20 lines
aiofranka log -n 100       # last 100 lines
aiofranka log -f           # follow (like tail -f)

Common flags

Most commands accept these flags:

Flag	Description
--ip IP	Robot IP address (default: last used, or 172.16.0.2)
--username USER	Franka Desk web UI username (default: saved or prompted)
--password PASS	Franka Desk web UI password (default: saved or prompted)
--protocol http|https	Web UI protocol (default: https)

Core Concepts

Server Mode vs Async Mode

	Server mode	Async mode
Class	FrankaRemoteController	FrankaController
API style	Synchronous (plain Python)	async/await
1kHz loop runs in	Subprocess (auto-managed)	Your process (asyncio task)
Blocking calls OK?	Yes — can't starve the loop	No — must stay under ~1ms
State reads	Shared memory (zero-copy)	Direct attribute access
Commands	ZMQ IPC (msgpack)	Direct method calls
Setup	unlock() + ctrl.start()	Single script
Best for	Heavy workloads (GPU inference, vision pipelines)	Lightweight scripts, rapid prototyping

Rate Limiting

Use set_freq() to enforce strict timing for command updates:

controller.set_freq(50)  # Set 50Hz update rate

# This will automatically sleep to maintain 50Hz timing
for i in range(100):
    controller.set("q_desired", compute_target())

State Access

Robot state is continuously updated at 1kHz and accessible via controller.state:

state = controller.state  # Thread-safe access
# Contains: qpos, qvel, ee, jac, mm, last_torque
print(f"Joint positions: {state['qpos']}")
print(f"End-effector pose: {state['ee']}")  # 4x4 homogeneous transform

Controllers

1. Impedance Control (Joint Space)

Controls joint positions with spring-damper behavior:

controller.switch("impedance")
controller.kp = np.ones(7) * 80.0   # Position gains
controller.kd = np.ones(7) * 4.0    # Damping gains

controller.set("q_desired", target_joint_angles)

Use case: Precise joint-space motions, compliant behavior

2. Operational Space Control (Task Space)

Controls end-effector pose in Cartesian space:

controller.switch("osc")
controller.ee_kp = np.array([300, 300, 300, 1000, 1000, 1000])  # [xyz, rpy]
controller.ee_kd = np.ones(6) * 10.0

desired_ee = np.eye(4)  # 4x4 homogeneous transform
desired_ee[:3, 3] = [0.4, 0.0, 0.5]  # Position
controller.set("ee_desired", desired_ee)

Use case: Cartesian trajectories, end-effector tracking

License

MIT License - see LICENSE file

Citation

If you use this library in your research, please cite:

@software{aiofranka,
  author = {Improbable AI Lab},
  title = {aiofranka: Asyncio-based Franka Robot Control},
  year = {2025},
  url = {https://github.com/Improbable-AI/aiofranka}
}

Acknowledgments

• Built on libfranka by Franka Emika
• Uses MuJoCo physics engine
• Trajectory generation with Ruckig