AI Programming for Robotics: Building Intelligent, Interactive Systems
- Perception: Gathering and interpreting sensory information
- Planning: Determining the optimal sequence of actions
- Control: Executing actions accurately and reliably
- Localization: Knowing the robot's position in the environment
- Mapping: Building a representation of the environment
AI Concept | Description | Example |
|---|---|---|
Perception | Interpreting sensory data | Object recognition using computer vision |
Planning | Determining optimal actions | Path planning for navigation |
Control | Executing actions accurately | Maintaining balance while walking |
Localization | Estimating robot position | Using SLAM to build a map |
Mapping | Creating environment representation | Generating a 3D point cloud |
AI Concept | Description | Example |
|---|---|---|
Perception | Interpreting sensory data | Object recognition using computer vision |
Planning | Determining optimal actions | Path planning for navigation |
Control | Executing actions accurately | Maintaining balance while walking |
Localization | Estimating robot position | Using SLAM to build a map |
Mapping | Creating environment representation | Generating a 3D point cloud |
- Deep Learning: Neural networks for complex tasks
- Computer Vision: Processing and interpreting images
- Path Planning: Finding optimal routes
- Reinforcement Learning: Learning through trial and error
- SLAM: Simultaneous Localization and Mapping
Algorithm | Description | Application |
|---|---|---|
Deep Learning | Neural networks for pattern recognition | Image classification, object detection |
Computer Vision | Image and video processing | Robot navigation, inspection |
A* Path Planning | Finding shortest path between two points | Robot navigation in known environments |
Reinforcement Learning | Learning optimal behavior through rewards | Robot manipulation, game playing |
SLAM | Building a map while localizing | Autonomous exploration, mapping |
Algorithm | Description | Application |
|---|---|---|
Deep Learning | Neural networks for pattern recognition | Image classification, object detection |
Computer Vision | Image and video processing | Robot navigation, inspection |
A* Path Planning | Finding shortest path between two points | Robot navigation in known environments |
Reinforcement Learning | Learning optimal behavior through rewards | Robot manipulation, game playing |
SLAM | Building a map while localizing | Autonomous exploration, mapping |
- Robot Operating System (ROS): A flexible framework for robot software development.
- TensorFlow/PyTorch: Machine learning frameworks for training AI models.
- Gazebo/V-REP: Simulation environments for testing robot software.
- Python: A versatile programming language for robotics.
- C++: A high-performance language for real-time control.
Framework/Tool | Description | Use Case |
|---|---|---|
ROS | Modular framework for robot software | Developing complex robotic systems |
TensorFlow | Machine learning framework | Training AI models for perception |
PyTorch | Machine learning framework | Training AI models for control |
Gazebo | 3D robot simulator | Testing robot algorithms in a virtual environment |
Python | General-purpose programming language | Scripting, data analysis, AI development |
Framework/Tool | Description | Use Case |
|---|---|---|
ROS | Modular framework for robot software | Developing complex robotic systems |
TensorFlow | Machine learning framework | Training AI models for perception |
PyTorch | Machine learning framework | Training AI models for control |
Gazebo | 3D robot simulator | Testing robot algorithms in a virtual environment |
Python | General-purpose programming language | Scripting, data analysis, AI development |
- Manufacturing: Assembly, inspection, material handling
- Healthcare: Surgery, rehabilitation, medication delivery
- Transportation: Autonomous vehicles, delivery robots
- Agriculture: Planting, harvesting, crop monitoring
- Exploration: Disaster response, deep-sea exploration
Industry | AI-Powered Application | Benefits |
|---|---|---|
Manufacturing | Automated assembly line | Increased efficiency, reduced costs |
Healthcare | Robot-assisted surgery | Improved precision, faster recovery |
Transportation | Self-driving cars | Increased safety, reduced congestion |
Agriculture | Autonomous harvesting | Increased yield, reduced labor |
Exploration | Underwater inspection robot | Data collection in hazardous environments |
Industry | AI-Powered Application | Benefits |
|---|---|---|
Manufacturing | Automated assembly line | Increased efficiency, reduced costs |
Healthcare | Robot-assisted surgery | Improved precision, faster recovery |
Transportation | Self-driving cars | Increased safety, reduced congestion |
Agriculture | Autonomous harvesting | Increased yield, reduced labor |
Exploration | Underwater inspection robot | Data collection in hazardous environments |
