Tianji Marvin

Tianji Marvin#

Tianji Marvin is a dual-arm platform from TianJi Robotics. The EmbodiChain preset keeps the source ACD joint and link names and provides two seven-joint arm control parts with optional parallel-jaw grippers.

Tianji Marvin dual-arm robot

Tianji Marvin

Key Features#

  • Dual seven-DOF arms with separate left_arm and right_arm control parts.

  • Optional parallel-jaw grippers with mimic joints, selected through with_gripper.

  • Source-compatible asset naming using the original ACD URDF joint and link names.

  • PyTorch FK/IK solvers with a documented tool-center-point transform for each arm.

  • Simulation-ready configuration for SimulationManager, including fixed base properties and configurable joint drives.

Robot Parameters#

Parameter

Description

Arm DOF

7 per arm, 14 total

Gripper variant

with_gripper=True adds left_hand and right_hand; the default is True

Gripper joints

Two finger joints per hand; finger 2 mimics finger 1

Arm root links

left_arm_base and right_arm_base

Gripper asset

TianjiMarvin/robot_with_ee_acd.urdf

Arm-only asset

TianjiMarvin/robot_acd.urdf

Physics root

Fixed base in the simulation preset

The two variants expose the following control parts:

Setting

Control parts

True (default)

left_arm, right_arm, left_hand, right_hand

False

left_arm, right_arm

Quick Initialization Example#

from embodichain.lab.sim import SimulationManager, SimulationManagerCfg
from embodichain.lab.sim.robots import TianjiMarvinCfg

config = SimulationManagerCfg(headless=False, device="cpu", num_envs=1)
sim = SimulationManager(config)

robot = sim.add_robot(
    cfg=TianjiMarvinCfg.from_dict({"with_gripper": True})
)

# Explicitly advance physics when the application is ready.
sim.update(step=1)

Use the arm-only model when the task supplies its own end effectors:

cfg = TianjiMarvinCfg.from_dict({"with_gripper": False})
robot = sim.add_robot(cfg=cfg)

Configuration Parameters#

Main Configuration Items#

  • with_gripper: Selects the complete gripper model or the arm-only ACD model. The field must be a boolean.

  • fpath: Optional URDF override. The same selected URDF is used for simulation and serial-chain FK/IK construction.

  • control_parts: Joint groups for the two arms and, when enabled, the two hands. Joint names retain the source asset naming.

  • solver_cfg: Per-arm PytorchSolverCfg entries. The default roots are left_arm_base and right_arm_base.

  • joint_drive_props: Simulation drive gains. The preset uses simulation defaults and does not claim to reproduce factory motor specifications.

TCP and FK/IK#

The source end links depend on the selected variant:

with_gripper

Left source end link

Right source end link

True

left_hand_tool_link

right_hand_tool_link

False

left_ee

right_ee

Both variants apply the same end-link-to-TCP transform. The TCP origin is translated 0.13 m along the source end link’s +X axis and rotated +90 degrees about that link’s Y axis:

T_end_link_tcp = [[ 0, 0, 1, 0.13],
                  [ 0, 1, 0, 0   ],
                  [-1, 0, 0, 0   ],
                  [ 0, 0, 0, 1   ]]

Solver FK returns T_root_tcp = T_root_end_link @ T_end_link_tcp, and solver IK expects the TCP pose relative to the arm root. Named Robot.compute_fk() and Robot.compute_ik() use the TCP pose in the local arena frame. If an application starts with a source end-link pose, convert it before calling IK:

T_arena_tcp = T_arena_end_link @ T_end_link_tcp

build_pk_serial_chain() returns raw seven-joint chains ending at the source links. Its FK omits the configured TCP transform; right-multiply by solver_cfg[part].tcp to obtain the solver TCP pose. To operate directly on source end-link poses, override both arm TCP transforms with identity matrices:

import numpy as np
from embodichain.lab.sim.robots import TianjiMarvinCfg

cfg = TianjiMarvinCfg.from_dict(
    {
        "with_gripper": False,
        "solver_cfg": {
            "left_arm": {"tcp": np.eye(4).tolist()},
            "right_arm": {"tcp": np.eye(4).tolist()},
        },
    }
)

Preview#

Run the preview and FK/IK smoke check in the project environment:

conda run -n embodichain python -m embodichain.lab.sim.robots.tianji_marvin --headless
conda run -n embodichain python -m embodichain.lab.sim.robots.tianji_marvin --headless --no-with-gripper

Omit --headless to open the simulation window and an interactive session.

References#

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