Getting Started with Pinocchio and MeshCat for reBot Arm B601-DM

traj_sim_geodesic

Pinocchio is an open-source library for robotics dynamics analysis and optimization. It provides efficient forward/inverse kinematics, dynamics calculations, and trajectory planning capabilities. MeshCat is a web-based 3D visualization tool that can display robot status and motion trajectories in real-time.

This project combines Pinocchio's powerful computing capabilities with MeshCat's intuitive visualization, providing a complete set of kinematic analysis and debugging tools for reBot Arm B601-DM.

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Project Features

Complete Kinematic Analysis
Supports Forward Kinematics (FK) and Inverse Kinematics (IK) calculations, able to solve the robot arm's end-effector pose in real-time.
Real-time 3D Visualization
Displays robot arm status and motion trajectories in real-time through MeshCat in the browser, no additional software required.
Trajectory Planning and Tracking
Implements SE(3) geodesic trajectory planning, supporting CLIK (Closed-Loop Inverse Kinematics) tracking control.
Gravity Compensation Control
Calculates joint gravity torque based on Pinocchio dynamics model, achieving the "floating" effect of the robot arm.
Open Source & Extensible
All code is open source, supporting users to customize control algorithms and visualization effects according to their needs.

Specifications

The hardware for this tutorial is provided by Seeed Studio

Parameter	Specification
Robot Arm Model	reBot Arm B601-DM
Degrees of Freedom	6-DOF + Gripper
Motor Model	Damiao DM4340 / DM4310
Communication Method	CAN Bus via USB-CAN Adapter
Operating Voltage	24V DC
Control Method	PC
Recommended Operating Temperature Range	0°C ～ 40°C

Bill of Materials (BOM)

Component	Quantity	Included
reBot Arm B601-DM Robotic Arm	1	✅
USB2CAN Serial Bridge	1	✅
Power Adapter (24V)	1	✅
USB-C Cable	1	✅
Gripper	1	✅

caution

Seeed Studio is only responsible for hardware quality. The tutorial is updated in strict accordance with official documentation. If you encounter unsolvable software or environmental issues, please consult the FAQ at the end of the document first, or contact customer service to join the SeeedStudio Lerobot communication group for inquiries.

Environment Requirements

Item	Requirement
Python	3.10+
Operating System	Ubuntu 22.04+
Communication Interface	USB2CAN Serial Bridge or CAN Interface

Installation Steps

Step 1. Install uv (if not installed)

curl -LsSf https://astral.sh/uv/install.sh | sh

Step 2. Sync Environment (Install All Dependencies)

git clone https://github.com/vectorBH6/reBotArm_control_py.git
cd reBotArm_control_py
uv sync

tip

uv sync will automatically create a virtual environment (if it doesn't exist) and install all dependencies according to pyproject.toml and uv.lock.

Debug Tools

Single Motor Console (`1_damiao_text.py`)

Direct motorbridge SDK single motor testing.

Usage:

uv run python example/1_damiao_text.py

Interactive Commands:

Command	Description
`enable` / `disable`	Enable/Disable
`set_zero`	Set zero position
`state`	View state

Zero Calibration & Angle Monitor (`2_zero_and_read.py`)

Automatically set all joint zeros and display joint angles in real-time.

Usage:

uv run python example/2_zero_and_read.py

Kinematics Tests

Forward Kinematics Test (`5_fk_test.py`)

Calculate end-effector pose from joint angles.

Input: 6 joint angles (degrees)

Output:

End-effector position (X, Y, Z) — Unit: meters
Rotation matrix (3×3)
Euler angles (Roll/Pitch/Yaw) — Unit: degrees

Example:

uv run python example/5_fk_test.py
> 0 0 0 0 0 0
> 45 -30 15 -60 90 180

Inverse Kinematics Test (`6_ik_test.py`)

Solve joint angles from desired end-effector pose.

Input Format:

Position only: <x> <y> <z> (meters)
Position + Orientation: <x> <y> <z> <roll> <pitch> <yaw> (degrees)

Example:

uv run python example/6_ik_test.py
> 0.25 0.0 0.15              # Position only
> 0.25 0.0 0.15 0 0 0        # Position + Orientation

Simulation Environment

Forward Kinematics Simulation (`sim/fk_sim.py`)

Interactive forward kinematics simulation, visualize robot arm pose by inputting joint angles in MeshCat.

Usage:

uv run python example/sim/fk_sim.py

Interactive Commands:

Input 6 joint angles (degrees), space separated
Example: 0 0 0 0 0 0
Example: 45 -30 15 -60 90 -180
q/quit/exit: Exit

Features:

Real-time display of end-effector position and orientation
Supports continuous input to test different poses
Formatted pose information output

Inverse Kinematics Simulation (`sim/ik_sim.py`)

Interactive inverse kinematics simulation, automatically solve joint angles from target pose and visualize.

Usage:

uv run python example/sim/ik_sim.py

Input Format:

Position only: x y z (meters)
Position+Orientation: x y z roll pitch yaw (radians)

Example:

> 0.25 0.0 0.25              # Position only
> 0.25 0.0 0.25 0 0 0        # Position+Orientation

Features:

Automatic judgment of IK convergence
Display iteration count and error
Real-time robot pose updates

Trajectory Planning Simulation (`sim/traj_sim.py`)

SE(3) geodesic based trajectory planning simulation, including CLIK tracking and MeshCat animation playback.

Usage:

uv run python example/sim/traj_sim.py

Interactive Commands:

Input: x y z [roll pitch yaw] (meters/radians)
Press Enter to use default configuration
q: Exit

Features:

Plan from current position to target position
Use minimum jerk trajectory profile
Real-time display of trajectory statistics
Complete trajectory animation playback in MeshCat
Display reference path (gray) and actual path (green)

Visualizer Tool (`sim/visualizer.py`)

MeshCat visualizer wrapper, providing unified robot display interface.

Main Features:

Load URDF model and display robot
Draw 3D polyline paths (reference/actual)
Display IK target pose (tricolor axes + sphere)
Support joint trajectory animation playback

Usage Example:

from example.sim.visualizer import Visualizer
viz = Visualizer()
viz.update(q)  # Update robot pose
viz.draw_path(points, "path_name", color)  # Draw path

Real Machine Control

Permission Setup

Before running real machine control examples, you need to set device permissions:

# Set serial device permission (Damiao USB2CAN)
sudo chmod 666 /dev/ttyACM0

# Or for CAN interface (e.g., can0)
sudo chmod 666 /dev/can0

IK Real-time Control (`7_arm_ik_control.py`)

Real-time end-effector control based on IK solver.

Interactive Commands:

Command	Description
`x y z [roll pitch yaw]`	Target end-effector pose
`state`	View state
`pos`	Current end-effector position
`q/quit/exit`	Exit

Usage:

uv run python example/7_arm_ik_control.py
> 0.3 0.0 0.2
> 0.3 0.1 0.25 0 0.5 0

Trajectory Planning Control (`8_arm_traj_control.py`)

SE(3) geodesic trajectory planning + CLIK tracking.

Input Format:

x y z [roll pitch yaw] [duration]

Parameters:

x, y, z: Target position (meters)
roll, pitch, yaw: Target orientation (radians)
duration: Movement duration (seconds), default 2.0s

Usage:

uv run python example/8_arm_traj_control.py
> 0.3 0.0 0.3 0 0.4 0 2.0

Gravity Compensation Control (`9_gravity_compensation.py`)

Compensates for joint gravity using Pinocchio dynamics model.

Control Law:

tau = g(q)          — Gravity feedforward
pos = current motor position  — Joint position follows current position
kp = 2,  kd = 1     — Unified stiffness/damping for all joints

Expected Behavior:

The robotic arm can "float" in any posture
Won't fall due to its own weight when released
Can be manually moved to any position

Usage:

uv run python example/9_gravity_compensation.py

Output:

Real-time display of expected torque for each joint (N·m)
Press Ctrl+C to stop and disconnect

FAQ

Encountering Permission denied error
Ensure you have executed sudo chmod 666 /dev/ttyACM0 or sudo chmod 666 /dev/can0 to set device permissions.
IK solving fails or results are abnormal
Check if the target pose is within the robot arm's workspace, ensure joint limit configuration is correct.
Gravity compensation effect is not good
This may be caused by structural errors and processing accuracy. The gravity compensation of this project depends on urdf and pinocchio. You can try to correct urdf to your actual measured parameters (you can ask ai for this step).

License

This project is open source under the MIT License.

Contact Us

Technical Support: Submit Issue
Repository: GitHub
Forum: Seeed Studio Forum

Reference Documents

If this project helps you, please give us a Star!

Project Features​

Specifications​

Bill of Materials (BOM)​

Environment Requirements​

Installation Steps​

Step 1. Install uv (if not installed)​

Step 2. Sync Environment (Install All Dependencies)​

Debug Tools​

Single Motor Console (1_damiao_text.py)​

Zero Calibration & Angle Monitor (2_zero_and_read.py)​

Kinematics Tests​

Forward Kinematics Test (5_fk_test.py)​

Inverse Kinematics Test (6_ik_test.py)​

Simulation Environment​

Forward Kinematics Simulation (sim/fk_sim.py)​

Inverse Kinematics Simulation (sim/ik_sim.py)​

Trajectory Planning Simulation (sim/traj_sim.py)​

Visualizer Tool (sim/visualizer.py)​

Real Machine Control​

IK Real-time Control (7_arm_ik_control.py)​

Trajectory Planning Control (8_arm_traj_control.py)​

Gravity Compensation Control (9_gravity_compensation.py)​

FAQ​

License​

Contact Us​

Reference Documents​

Project Features

Specifications

Bill of Materials (BOM)

Environment Requirements

Installation Steps

Step 1. Install uv (if not installed)

Step 2. Sync Environment (Install All Dependencies)

Debug Tools

Single Motor Console (`1_damiao_text.py`)

Zero Calibration & Angle Monitor (`2_zero_and_read.py`)

Kinematics Tests

Forward Kinematics Test (`5_fk_test.py`)

Inverse Kinematics Test (`6_ik_test.py`)

Simulation Environment

Forward Kinematics Simulation (`sim/fk_sim.py`)

Inverse Kinematics Simulation (`sim/ik_sim.py`)

Trajectory Planning Simulation (`sim/traj_sim.py`)

Visualizer Tool (`sim/visualizer.py`)

Real Machine Control

IK Real-time Control (`7_arm_ik_control.py`)

Trajectory Planning Control (`8_arm_traj_control.py`)

Gravity Compensation Control (`9_gravity_compensation.py`)

FAQ

License

Contact Us

Reference Documents