ATI Axia F/T Sensor Python Driver

Easy Integration of ATI Axia Force-Torque Sensors into Python Projects

🔗 GitHub Link

The ATI Axia Python Driver is a lightweight and efficient Python package for communicating with ATI Axia force-torque sensors over Ethernet. It simplifies sensor configuration, data streaming, and ROS integration, without the need for additional C++ dependencies. This package has been used for logging data, communicating measurements to other ROS packages, and detecting contact when interacting with objects.

Key Features:

  • Easy Sensor Communication: Connect to an Axia sensor using just its IP address—no complex setup required.
  • Flexible Data Acquisition: Supports both batch and continuous streaming modes, with optional filtering.
  • ROS Integration: Publishes force-torque data to /AxiaWrench at rates up to 7.7 kHz using WrenchStamped messages.
  • Configurable and Persistent Settings: Load, modify, and store sensor configurations using YAML files.

Usage

Once installed, the driver allows you to connect to the sensor and retrieve real-time force-torque data with minimal setup. Here’s a quick example:

from AxiaDriver.configuration import AxiaConfiguration
from AxiaDriver.communication import AxiaCommunication
from AxiaDriver.data_management import Recorder, Filtering  

# Connect to the sensor using its IP address
sensor_ip = '192.168.3.101'
com = AxiaCommunication(sensor_ip)
com.connect()

# Read and save the current sensor configuration
config = com.read_configuration()
config.save_to_yaml('current_config.yaml')

# Write a new configuration to the sensor
config = AxiaConfiguration.load_from_yaml('new_onfig.yaml')
com.write_configuration(config)

# Record five seconds of (filtered) force-torque data to a CSV file
# while publishing the data to the /AxiaWrench ROS topic.
filter = Filtering.MovingAverageFilter(window_length=8)
recorder = Recorder('output.csv', config, filter=filter, ros_publish=True)
recorder.start_recording()
time.sleep(5)
recorder.stop_recording()

For more details, visit the GitHub repository, where you’ll find installation instructions, API usage, and additional examples.