Why Humanoid Robots Are Booming Yet Hard for the Average Person to Join – An Industry Chain Overview

1. Historical Origins

Humanoid robots are not a 2025 phenomenon; early concepts date back to the Western Zhou period in China and the mechanical automata of the Warring States era. In 1920, Czech writer Karel Capek introduced the term “robot” in his play R.U.R. , foreseeing societal impacts.

2. Safety Protocols and Consensus

In 1950, Isaac Asimov proposed the Three Laws of Robotics to prevent harm to humans. Subsequent academic conferences, such as the 1967 Japanese robotics symposium, defined robots as flexible machines with seven characteristic traits (mobility, individuality, intelligence, etc.) and later refined the definition to a programmable, autonomous system capable of tasks like manipulation and navigation.

3. Development History and Classification

Robots are commonly divided into three generations:

First generation – Teach‑replay (e.g., 1947 Oak Ridge remote‑controlled robot, 1962 PUMA).

Second generation – Sensing robots that add force, touch, vision, and auditory perception.

Third generation – Intelligent robots with multi‑sensor fusion, reasoning, and autonomous decision‑making.

Control methods further split into operation‑type, program‑controlled, teach‑replay, CNC‑type, sensory‑controlled, adaptive, and learning‑controlled robots.

4. Industry Chain – Upstream, Midstream, Downstream

Upstream components and software dominate cost (45‑60% for execution systems, 10‑15% for perception):

High‑precision screws (rolling‑contact ball screws).

Motors: frameless torque motors for joints, hollow‑cup motors for dexterous hands (e.g., Mingzhi Electric, market‑share leader).

Sensors: six‑axis force/torque, 3D vision, LiDAR, IMU, ultrasonic, infrared.

Reducers: harmonic (light‑load, high precision), RV (high load), planetary (compact, efficient).

Controllers and AI chips: Nvidia Jetson, Qualcomm RB5, Horizon, Huawei Ascend.

Software platforms: ROS, RT‑Thread, custom real‑time OS.

Midstream – Robot body manufacturing includes:

Mechanical design (joint layout, material selection).

Motion‑control algorithms and kinematics.

Perception module integration (vision, force, tactile).

Hardware integration (assembling motors, reducers, encoders).

Modular production for scalability.

System integration of OS, control algorithms, and perception models.

Testing: performance verification, reliability under extreme conditions, and full‑process quality control.

Downstream applications are grouped into three major scenarios:

Industrial manufacturing – flexible production, hazardous environment tasks, fire‑rescue.

Commercial services & public utilities – labor shortage relief, medical and elderly assistance.

Home services – cleaning, companionship, entertainment.

Specific sectors include medical‑health (surgical assistance, rehabilitation), logistics‑warehousing (搬运, sorting), education‑research (teaching demos, skill training), life‑service (cleaning, elder‑care), and special‑task robots (fire‑fighting, inspection, exploration).

5. Business Models

Whole‑machine sales : one‑time hardware fee plus annual maintenance.

RaaS (Robot‑as‑a‑Service) : usage‑based charging (hourly/monthly), lowering entry barriers for logistics, retail, and elder‑care.

Custom solutions : hardware + software + scenario adaptation for high‑end industries (automotive, nuclear, aerospace).

Value‑added subscription : OTA updates, algorithm optimisation, data analytics, remote operation for recurring revenue.

6. Challenges and Opportunities

The rapid rise of robotics parallels AI‑driven automation, raising concerns about job displacement similar to the 2008 financial crisis. While robots offer cost advantages—no salaries, continuous operation, no emotional fatigue—they also lack human empathy and adaptability. The industry therefore faces a dual challenge: ensuring safety, ethical deployment, and developing new skill sets for workers to transition into AI‑augmented roles.

Overall, the humanoid‑robot market is at a crossroads where technological breakthroughs, component cost structures, and evolving business models converge, presenting both significant growth potential and societal implications.