Potential use cases for humanoid robots: Disaster response, caregiving and beyond - Robotics & Automation News

More recently, BMW began testing another humanoid robot called Aeon, developed by the robotics division of Hexagon, at its Leipzig plant in Germany. The robot is designed to support workers by performing repetitive tasks and moving components around the factory floor.

Other automakers are exploring similar approaches. Mercedes‑Benz has invested in Apptronik and is testing humanoid robots in production environments for tasks such as moving parts and performing inspections.

In these settings, humanoids are not replacing traditional industrial robots. Instead, they are being evaluated as flexible assistants capable of performing tasks that are difficult to automate with fixed machinery.

Disaster response: The original vision ### Manufacturing: the first real-world deployments

Manufacturing plants are emerging as another early test environment for humanoid robots.

Unlike warehouses, factories are structured environments with predictable workflows and strict safety systems – conditions that make them easier for robots to navigate.

Automakers have begun exploring humanoid robots as a supplement to existing automation.

For example, BMW has launched pilot projects involving humanoid robots in its factories. At the company’s Spartanburg plant in the United States, robots from Figure AI were tested on assembly tasks and operated on daily shifts during trials. Several companies are targeting this sector:

Agility Robotics is developing its Digit humanoid robot for logistics operations, focusing on tasks such as tote handling and material movement. Figure AI has been testing humanoid robots in industrial environments including warehouse-style operations. Apptronik has positioned its Apollo robot for logistics and manufacturing tasks.

However, warehouses are already heavily automated using other technologies – including autonomous mobile robots, robotic arms, and conveyor systems.

For humanoids to succeed in logistics, they must demonstrate that they can perform tasks more flexibly or more economically than existing automation.

Manufacturing: the first real-world deployments