robot-kinematics 1.1.0

A comprehensive robotics kinematics library with URDF and PyBullet integration

Robot Kinematics Library

A comprehensive, production-ready robotics kinematics library for Python that provides forward and inverse kinematics, Jacobian calculations, and advanced robotics analysis tools with URDF and PyBullet integration.

Author: Sherin Joseph Roy
Email: [e-mail]
Repository: https://github.com/Sherin-SEF-AI/robot-kinematics

Features

• Forward Kinematics: DH parameters, URDF parsing, multiple robot configurations
• Inverse Kinematics: Numerical, analytical, and hybrid solvers
• Jacobian Analysis: Geometric and analytical Jacobians, singularity detection
• Robot Types: UR5, Panda, SCARA, Delta, KUKA KR5, Stewart platform, mobile manipulators
• Advanced Features: Workspace analysis, singularity avoidance, performance optimization
• Integration: URDF import/export, PyBullet visualization and animation
• High Performance: JIT compilation, caching, vectorized operations

Installation

Basic Installation

pip install robot-kinematics

With Visualization Support

pip install robot-kinematics[visualization]

Full Installation (All Dependencies)

pip install robot-kinematics[full]

Quick Start

import numpy as np
from robot_kinematics.robots.serial import UR5Manipulator, KUKAKR5Manipulator
from robot_kinematics.inverse.numerical import NumericalIK
from robot_kinematics.core.transforms import Transform

# Create a UR5 robot
ur5 = UR5Manipulator()
print(f"Robot: {ur5.config['name']}")
print(f"Number of joints: {ur5.n_joints}")

# Forward kinematics
joint_config = np.array([0, 0, 0, 0, 0, 0])  # Home position
pose = ur5.forward_kinematics(joint_config)
print(f"End-effector position: {pose.position}")

# Inverse kinematics
target_pose = Transform(position=np.array([0.4, 0.0, 0.5]))
ik_solver = NumericalIK(robot=ur5, method="damped_least_squares")
solution, success, error = ik_solver.solve(target_pose, joint_config)

if success:
    print(f"IK solution: {solution}")
    print(f"Error: {error}")

# Create KUKA KR5 robot
kuka = KUKAKR5Manipulator()
print(f"KUKA KR5 robot: {kuka.config['name']}")

URDF Integration

from robot_kinematics.integration.urdf_utils import load_robot_from_urdf
from robot_kinematics.robots.serial import SerialManipulator

# Load robot from URDF file
config = load_robot_from_urdf("robot.urdf")
robot = SerialManipulator(config)

PyBullet Visualization

from robot_kinematics.integration.pybullet_utils import connect_gui, create_kuka_kr5_pybullet, animate_trajectory

# Connect to PyBullet GUI
connect_gui()

# Load robot model
robot_id = create_kuka_kr5_pybullet()

# Animate trajectory
joint_trajectory = [q1, q2, q3, ...]  # List of joint configurations
animate_trajectory(robot_id, joint_trajectory, dt=0.05)

Documentation

For detailed documentation, examples, and API reference, visit our documentation.

Supported Robot Types

• Serial Manipulators: UR5, Panda, SCARA, Delta, KUKA KR5
• Parallel Robots: Stewart platform, Delta parallel
• Mobile Manipulators: Dual-arm systems, mobile bases

Performance Features

• JIT Compilation: Using Numba for accelerated computations
• Caching: Thread-safe caching for repeated calculations
• Vectorization: Optimized NumPy operations
• Memory Management: Efficient memory usage for large-scale operations

Examples

Check the examples/ directory for comprehensive examples:

• basic_usage.py - Basic kinematics operations
• simple_advanced_example.py - Trajectory planning and analysis
• pybullet_kuka_kr5_demo.py - PyBullet visualization demo
• urdf_import_export_demo.py - URDF integration demo

Testing

Run the test suite:

pytest tests/

Contributing

We welcome contributions! Please see our contributing guidelines for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

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

@software{robot_kinematics,
  title={Robot Kinematics Library},
  author={Sherin Joseph Roy},
  year={2024},
  url={https://github.com/Sherin-SEF-AI/robot-kinematics}
}