User Guide — ManipulaPy 1.1.0 Documentation
Description: Welcome to the comprehensive ManipulaPy User Guide! This section provides detailed tutorials and explanations for all aspects of robotic manipulation using ManipulaPy. Quick Navigation: 📚 Complete ...

# User Guide

Welcome to the comprehensive ManipulaPy User Guide! This section provides detailed tutorials and explanations for all aspects of robotic manipulation using ManipulaPy.

## 🎓 Master Modern Robotics

From basic kinematics to advanced GPU-accelerated control systems, this guide will take you from beginner to expert.

13 Comprehensive Guides
60+ Code Examples
120+ Practical Tips

## 📚 Complete Guide Overview

Core Robotics Fundamentals

- Kinematics User Guide
  - What is Robot Kinematics?
  - Mathematical Foundation
  - SerialManipulator Class
  - Creating a Robot Model
  - Forward Kinematics
  - Inverse Kinematics
  - Jacobian Matrix
  - Velocity Kinematics
  - State Management
  - Working Examples
  - Common Issues and Solutions
  - Best Practices
  - Next Steps
- Dynamics User Guide
  - Introduction to Robot Dynamics
  - Setting Up Robot Dynamics
  - Mass Matrix Computation
  - Velocity-Dependent Forces
- Control Module User Guide
  - Overview
  - Mathematical Foundation
  - Installation and Setup
  - Quick Start
  - Controller Types
  - Advanced Features
  - Tuning Methods
  - Plotting and Analysis
  - Cartesian Space Control
  - Examples
  - Troubleshooting
  - API Reference
  - Additional Resources
- URDF Processor User Guide
  - Introduction
  - Basic Usage
  - URDFToSerialManipulator Class
  - Core Methods
  - Joint Limit Handling
  - Utility Methods
  - Working Example
  - Error Handling
  - Best Practices
  - Summary

Motion Planning & Simulation

- Trajectory Planning User Guide
  - Introduction
  - Joint-Space Time Scaling
  - Dynamics-Aware Torque Computation
  - Potential-Field Collision Avoidance
  - Basic Usage
  - TrajectoryPlanning Class
  - Core Methods
  - Dynamics Integration
  - Trajectory Visualization
  - Advanced Features
  - Performance Optimization
  - Real-Time Applications
  - Practical Applications
  - Best Practices
  - Summary
- Simulation Module User Guide
  - Installation and Setup
  - Quick Start
  - Module API Reference
  - Advanced Examples
  - Advanced Configuration
  - Performance Optimization
  - Troubleshooting Guide
  - Best Practices
  - Integration with Other Modules
  - See Also
- Singularity Analysis User Guide
  - Theoretical Background
  - Installation and Setup
  - Quick Start
  - Module API Reference
  - Advanced Analysis Examples
  - Performance Optimization
  - Troubleshooting Guide
  - Validation and Testing
  - Best Practices
  - See Also
- Collision Checker Module User Guide
  - Introduction
  - Mathematical Background
  - Class Reference
  - Installation
  - Usage Examples
  - Advanced Topics
  - Troubleshooting
  - References
- Potential Field Module User Guide
  - Introduction to Potential Fields
  - Class Reference
  - Usage Examples
  - Advanced Topics
  - Troubleshooting
  - References

Perception & Intelligence

- Perception User Guide
  - Overview
  - Key Features
  - Getting Started
  - Core Functionality
  - Data Flow Architecture
  - Advanced Applications
  - Performance Optimization
  - Error Handling and Robustness
  - Best Practices
  - Common Issues and Solutions
  - See Also

Advanced Topics

- Singularity Analysis User Guide
  - Theoretical Background
  - Installation and Setup
  - Quick Start
  - Module API Reference
  - Advanced Analysis Examples
  - Performance Optimization
  - Troubleshooting Guide
  - Validation and Testing
  - Best Practices
  - See Also
- CUDA Kernels User Guide
  - What is GPU Acceleration?
  - Mathematical Foundation
  - Installation and Setup
  - Available CUDA Kernels
  - Using GPU Acceleration
  - Performance Optimization
  - CPU Fallback
  - Troubleshooting
  - Best Practices
  - Integration with ManipulaPy
  - Working Examples
  - When to Use GPU Acceleration
  - Getting Started Checklist
  - Conclusion

## 🗺️ Learning Pathways

Choose your learning path based on your experience level and goals:

🌱

### Complete Beginner

New to robotics? Start here!

1
Kinematics Basics

Learn forward and inverse kinematics fundamentals

2
Robot Models

Load and work with robot URDF files

3
Virtual Robots

Simulate robots in PyBullet

4
Motion Planning

Plan smooth robot motions

🎯

### Robotics Engineer

Ready for advanced control?

1
Robot Dynamics

Understand forces, torques, and physics

2
Control Systems

Implement PID, computed torque control

3
Safety Systems

Collision detection and avoidance

4
Singularity Analysis

Analyze robot workspace and limitations

🚀

### Performance Expert

Master GPU acceleration!

1
CUDA Programming

GPU acceleration fundamentals

2
GPU Trajectories

Accelerated motion planning

3
Field Methods

Advanced obstacle avoidance

4
Optimization

Performance tuning techniques

👁️

### Vision & Perception

Master intelligent robotics!

1
Vision Systems

Camera setup, calibration, and processing

2
Perception Pipeline

Object detection and environmental understanding

3
Intelligent Planning

Perception-aware motion planning

4
Adaptive Control

Reactive and vision-guided control

## 📖 Guide Categories

### Core Robotics

Essential concepts every robotics engineer should master:

🔧

#### Kinematics

Difficulty: Beginner

Robot geometry, forward/inverse kinematics, Jacobians, and workspace analysis.

📊 Workspace Visualization
⚖️

#### Dynamics

Difficulty: Intermediate

Mass matrices, inverse/forward dynamics, Coriolis forces, and gravity compensation.

🔄 Smart Caching ⚡ GPU Accelerated
🎛️

#### Control Systems

Difficulty: Intermediate

PID control, computed torque, adaptive controllers, and auto-tuning.

🎯 Auto-tuning 📈 Performance Analysis
🤖

#### Robot Models

Difficulty: Beginner

Load URDF files, extract robot parameters, and create manipulator objects.

📁 URDF Support 🔧 Built-in Models

### Motion Planning & Simulation

Advanced motion planning and realistic simulation:

🛤️

#### Trajectory Planning

Difficulty: Intermediate

CUDA-accelerated joint and Cartesian trajectory generation with collision avoidance.

⚡ CUDA Kernels 🚧 Collision Avoidance
🎮

#### PyBullet Simulation

Difficulty: Beginner

Physics simulation, trajectory execution, and interactive robot control.

🎯 Real-time Control 📊 Visualization
🛡️

#### Collision Detection

Difficulty: Intermediate

Self-collision detection, environment obstacles, and safety monitoring.

🔍 Convex Hull ⚡ Fast Detection
🌊

#### Potential Fields

Difficulty: Advanced

Artificial potential fields for path planning and obstacle avoidance.

🧲 Attractive Fields ⚡ Repulsive Forces

### Perception & Intelligence

Computer vision, environmental understanding, and intelligent robot behavior:

📷

#### Vision Systems

Difficulty: Intermediate

Camera setup, stereo vision, depth processing, and multi-camera systems.

📐 Stereo Vision 🎛️ PyBullet Debug
🧠

#### Perception Pipeline

Difficulty: Advanced

Object detection, 3D clustering, environmental understanding, and robot integration.

🔍 YOLO Detection 🌐 3D Clustering

### Advanced Topics

Cutting-edge techniques for performance and analysis:

⚠️

#### Singularity Analysis

Difficulty: Advanced

Workspace analysis, manipulability ellipsoids, and singularity avoidance.

📊 Workspace Mapping 🎯 Monte Carlo
🚀

#### GPU Acceleration

Difficulty: Expert

Custom CUDA kernels, parallel processing, and performance optimization.

⚡ 50x Speedup 🔧 Custom Kernels

## 🎯 Quick Reference

#### 🚀 Getting Started

- Installation Guide
- First Robot Analysis
- Built-in Robot Models
- Your First Simulation

#### ⚡ Performance

- CUDA Setup
- GPU Trajectories
- Smart Caching
- Optimization Tips

#### 🔧 Common Tasks

- Solve Inverse Kinematics
- Implement PID Control
- Plan Trajectories
- Check Collisions

#### 👁️ Perception

- Setup Cameras
- Detect Obstacles
- Data Flow Pipeline
- Stereo Processing

#### 🎓 Advanced Topics

- Computed Torque Control
- Manipulability Analysis
- Potential Field Planning
- Custom CUDA Kernels

## 💡 Study Tips

📚

#### Follow the Order

The guides are designed to build on each other. Start with Kinematics and work your way through systematically.

💻

#### Code Along

Each guide includes working code examples. Type them out yourself - don't just copy-paste!

🧪

#### Experiment

Modify the examples, try different parameters, and break things. Learning happens through experimentation.

📊

#### Visualize

Use the plotting functions extensively. Understanding robotics requires good spatial intuition.

👁️

#### See & Think

Use the Vision and Perception modules to add intelligence to your robots. Modern robotics is perception-driven!

## 🆘 Need Help?

If you get stuck:

1. Check the Examples - Each guide has complete working examples

2. API Reference - Detailed function documentation in 🔧 API Reference Guide

3. GitHub Issues - Report bugs or ask questions on GitHub