ROS (Robot Operating System)

ROS is built around a distributed computing model where functionality is divided among multiple processes:

Nodes:
Individual processes that perform computation. A robot might have separate nodes for:
- Motor control
- Sensor processing
- Path planning
- User interface

Topics:
Named buses for asynchronous message passing. Nodes publish messages to topics and subscribe to receive messages. This decoupled architecture allows flexible system composition.

Services:
Synchronous request/response communication for operations that need acknowledgment or return values.

Actions:
Extended services for long-running tasks with feedback and cancellation support—ideal for robot motions.

Parameters:
Configuration values stored on a parameter server and accessed by nodes at runtime.

Example Topic Communication:
```python
# Publisher node
import rospy
from geometry_msgs.msg import Twist

rospy.init_node('velocity_commander')
pub = rospy.Publisher('/cmd_vel', Twist, queue_size=10)

vel = Twist()
vel.linear.x = 0.5 # Move forward
pub.publish(vel)

# Subscriber node (separate process)
def callback(msg):
print(f"Received velocity: {msg.linear.x}")

rospy.Subscriber('/cmd_vel', Twist, callback)
```

The ROS ecosystem provides building blocks for most robotics applications:

Navigation Stack:
Complete solution for autonomous mobile robot navigation:
- SLAM: Simultaneous Localization and Mapping (gmapping, cartographer)
- AMCL: Adaptive Monte Carlo Localization
- move_base: Path planning and obstacle avoidance
- costmap_2d: Environmental representation

MoveIt:
Motion planning framework for robotic arms:
- Kinematic solvers for inverse kinematics
- Collision detection and avoidance
- Trajectory generation
- Integration with popular robot arms

Perception:
- image_pipeline: Camera calibration and processing
- pcl_ros: Point cloud processing integration
- ar_track_alvar: Augmented reality marker tracking

Visualization and Debugging:
- RViz: 3D visualization of robot state, sensors, and plans
- rqt: Modular GUI framework with plugins for plotting, logging, and configuration
- rosbag: Record and playback message streams for testing

Simulation:
- Gazebo: High-fidelity physics simulation
- Stage: Lightweight 2D simulation for multi-robot systems

Development Tools:
- catkin/colcon: Build systems for compiling packages
- roslaunch: System startup and configuration
- rostopic/rosservice: Command-line introspection tools

ROS 2 represents a ground-up redesign addressing limitations for industrial deployment:

Key Improvements:

Real-Time Support:
Built on DDS (Data Distribution Service), ROS 2 can meet real-time requirements with proper configuration. This enables use in production systems where ROS 1's timing was insufficient.

Security:
Native support for authentication, encryption, and access control. Essential for industrial and safety-critical applications.

Multi-Platform:
Official support for Linux, Windows, and macOS. Embedded systems support through micro-ROS.

Quality of Service:
Configure reliability, durability, and deadline requirements per topic. Critical for systems with varying network conditions.

Lifecycle Management:
Standardized node states (unconfigured, inactive, active, finalized) enable coordinated system startup and shutdown.

Migration Considerations:
- ROS 1 reaches end-of-life in 2025
- Most new projects should start with ROS 2
- ros1_bridge enables gradual migration
- Learning ROS 2 now is investment in the future

ROS 2 Distributions:
- Humble Hawksbill (LTS, recommended for production)
- Iron Irwini (latest features)
- Future: Jazzy Jalisco (2024)

ROS adoption is accelerating in industrial settings:

Manufacturing Applications:
- Mobile Robots: AMRs for material transport use ROS navigation
- Bin Picking: Combining MoveIt with vision for random part picking
- Inspection: Autonomous inspection using ROS perception packages
- Collaborative Robots: ROS drivers for Universal Robots, FANUC, ABB

Companies Using ROS:
- Amazon Robotics (warehouse automation)
- Boston Dynamics (mobile robots)
- Universal Robots (collaborative arms)
- Fetch Robotics (AMRs)
- Clearpath Robotics (research platforms)
- Many startups and integrators

Career Opportunities:

ROS Developer: $80,000-$140,000
Building applications using ROS frameworks. Requires proficiency in Python and/or C++, understanding of ROS architecture, and domain knowledge.

Robotics Software Engineer: $100,000-$160,000
Broader role including system architecture, algorithm development, and integration.

Perception Engineer: $110,000-$170,000
Specializing in vision and sensor processing within ROS.

Learning Resources:
- ROS Wiki tutorials (free, comprehensive)
- The Construct (online courses with simulation)
- Programming Robots with ROS (O'Reilly book)
- University courses (many use ROS in robotics curricula)

Portfolio Projects:
- Implement SLAM on a mobile robot
- Create a MoveIt configuration for a robot arm
- Develop a custom perception pipeline
- Contribute to open-source ROS packages