Robotics has been 'the future' for decades without major mainstream adoption. However, specific domains are now seeing deployment: warehouse automation, autonomous vehicles, surgical robots, and delivery drones. The shift from 'nearly ready' to 'economically viable' is finally happening.

Warehouse automation is practical and deployed. Robots handle repetitive tasks (picking, packing, moving inventory) that humans find tedious and error-prone. Companies like Amazon and DHL have invested billions. The ROI is clear: robots work 24/7, don't require breaks, and reduce injury rates. The economics favor automation in high-throughput environments.

Autonomous vehicles remain challenging but progressing. Self-driving cars are more complex than robots in controlled environments like warehouses. They must handle unlimited scenarios, edge cases, and interact with unpredictable humans. Companies like Waymo (acquired by Alphabet) operate autonomous taxi services in Phoenix and San Francisco. The technology works but remains limited in scope and weather conditions.

Challenges in real-world robotics: Physical world has unlimited variation. Labs have controlled conditions. Real-world robots must handle unexpected situations. Sensor failures, edge cases, and adversarial interactions occur. Machine learning enables adaptation but requires careful design. Humans remain better at generalization; robots remain better at specific, repetitive tasks.

Surgical robots (da Vinci) are widely deployed, enabling minimally invasive surgery. The surgeon controls a robot remotely, providing precision humans can't achieve. The combination of human decision-making and robotic precision is powerful. This model—human + robot collaboration—is more practical than fully autonomous systems for high-stakes scenarios.

Drone delivery remains largely aspirational. Companies like Amazon have conducted trials, but regulatory frameworks are evolving slowly. Drones are excellent at delivering small packages over short distances. Whether that's valuable enough to justify the infrastructure remains unclear.

The software challenges in robotics are significant. ROS (Robot Operating System) provides abstractions for sensor input, decision logic, and motor control. Simulation (Gazebo) enables testing before physical deployment. However, sim-to-real transfer remains difficult—simulations lack the edge cases and noise of the real world.

The future involves increasing autonomy in narrow domains while maintaining human oversight for high-stakes decisions. Robots handling warehouse inventory while humans handle exceptions. Drones delivering packages while humans override in unusual situations. Surgical robots enabling human surgeons to be more precise. This human-robot collaboration is likely more practical than fully autonomous systems.