I2RT Python API

A Python client library for interacting with I2RT products — designed for learning-based robotics, teleoperation, and real-world deployment.

📚 Full documentation: doc.i2rt.com

Features

• Plug-and-play Python interface for YAM arms and Flow Base
• Real-time robot control via CAN bus (DM series motors)
• MuJoCo gravity compensation, simulation, and URDF/MJCF models
• Gripper force control and auto-calibration
• Bimanual teleoperation and trajectory record & replay
• Policy-deployment ready — works with standard robot learning pipelines

Installation

git clone https://github.com/i2rt-robotics/i2rt.git && cd i2rt
curl -LsSf https://astral.sh/uv/install.sh | sh
source $HOME/.local/bin/env
uv venv --python 3.11
source .venv/bin/activate

sudo apt update
sudo apt install build-essential python3-dev linux-headers-$(uname -r)
uv pip install -e .

CAN Bus Setup

# Check detected CAN devices
ls -l /sys/class/net/can*

# Bring up interface at 1 Mbit/s
sudo ip link set can0 up type can bitrate 1000000

# Auto-enable on boot
sudo sh devices/install_devices.sh

# Reset unresponsive adapter
sh scripts/reset_all_can.sh

YAM Arm

Arm variants

Every arm is six-DOF. Pick one with --arm on any CLI, or arm_type= in Python. A hardware revision is its own variant — yam_ultra_2 is revision 2 of the YAM Ultra.

Arm	--arm value	Arm mass	Chain length	Notes
YAM	yam	4.292 kg	0.807 m	Model docs
YAM Pro	yam_pro	4.349 kg	0.798 m	Model docs
YAM Ultra	yam_ultra	4.521 kg	0.813 m	Model docs
YAM Ultra 2	yam_ultra_2	4.597 kg	0.813 m	Revision 2 — kinematically identical to yam_ultra; revised link3/link4 inertials and a DM4340 on joint 4. Model docs
Big YAM	big_yam	5.307 kg	1.060 m	Model docs
(none)	no_arm	—	—	Gripper-only robot

"Arm mass" excludes the gripper and tips. "Chain length" is the sum of the parent-to-child joint-origin translation norms — a measure of the kinematic chain, not of reach. Each arm's model README tabulates full masses, COMs, inertias, joint frames, DH parameters, and screw axes.

Zero-gravity mode

python i2rt/robots/motor_chain_robot.py --channel can0 --arm yam --gripper linear_4310

Python API

from i2rt.robots.get_robot import get_yam_robot
from i2rt.robots.utils import ArmType, GripperType
import numpy as np

robot = get_yam_robot(
    channel="can0",
    arm_type=ArmType.YAM,
    gripper_type=GripperType.LINEAR_4310,
)

# Read joint positions (radians)
q = robot.get_joint_pos()   # shape: (6,)

# Command a target configuration
robot.command_joint_pos(np.zeros(6))

Leader-follower teleoperation

# Follower arm
python examples/minimum_gello/minimum_gello.py --gripper linear_4310 --mode follower --can-channel can0 --bilateral-kp 0.2

# Leader arm (teaching handle)
python examples/minimum_gello/minimum_gello.py --gripper yam_teaching_handle --mode leader --can-channel can1 --bilateral-kp 0.2

• Top button (press once): enable synchronisation — follower tracks leader
• Top button (press again): disable synchronisation
• --bilateral-kp controls resistance felt on the leader (0.1–0.2 recommended)

To inspect leader arm output:

python scripts/run_yam_leader.py --channel $CAN_CHANNEL

MuJoCo visualiser

python examples/minimum_gello/minimum_gello.py --mode visualizer_local

Gripper Types

Gripper	Motor	Notes
crank_4310	DM4310	Zero-linkage crank — minimises gripper width
linear_3507	DM3507	Lightweight linear; start closed or run calibration
linear_4310	DM4310	Standard linear; slightly more force than 3507
flexible_4310	DM4310	Linear with flexible soft tips for compliant grasps
yam_teaching_handle	—	Leader arm handle with trigger + 2 buttons.
no_gripper	—	Bare terminal mount; no gripper motor on the chain

The linear grippers require calibration because their motor travels more than 2π radians over the full stroke — either start with the gripper fully closed, or run the calibration routine.

Flow Base

# Joystick demo
python i2rt/flow_base/flow_base_controller.py

from i2rt.flow_base.flow_base_client import FlowBaseClient

client = FlowBaseClient(host="172.6.2.20")
client.set_target_velocity([0.1, 0.0, 0.0], frame="local")

Examples

Example	Location
Bimanual lead-follower	examples/bimanual_lead_follower/
Record & replay trajectory	examples/record_replay_trajectory/
Single motor PD control	examples/single_motor_position_pd_control/
MuJoCo control interface	examples/control_with_mujoco/
Viser (browser) control interface	examples/control_with_viser/
Drive Flow Base from Viser	examples/drive_flow_base_viser/
Plot Flow Base telemetry in Rerun	examples/plot_flow_base_rerun/

Advanced: Motor Configuration

Safety timeout

The factory default is a 400 ms timeout — motors enter damping mode if no command is received within 400 ms.

# Disable timeout (advanced users only — run twice)
python i2rt/motor_config_tool/set_timeout.py --channel can0
python i2rt/motor_config_tool/set_timeout.py --channel can0

# Re-enable timeout
python i2rt/motor_config_tool/set_timeout.py --channel can0 --timeout

⚠️ Without the timeout, a failed gravity-compensation loop can produce uncontrolled torque. If you disable it, always initialise with a PD target:

robot = get_yam_robot(channel="can0", zero_gravity_mode=False)

Zero motor offsets

python i2rt/motor_config_tool/set_zero.py --channel can0 --motor_id 1

Run for each motor ID (1–6 for a standard YAM).

Contributing

Pull requests welcome. Open an issue to request examples or report bugs.

License

MIT License — see LICENSE.

Support

• Email: support@i2rt.com
• Sales: sales@i2rt.com

Acknowledgments

• TidyBot++ — Flow Base hardware and control inspired by TidyBot++
• GELLO — Teleoperation design inspired by GELLO