What will it take to bring humanoid robots into the real world? Read our experts’ insights

Key takeaways:

• Semiconductors are the critical enabler for scaling humanoid robots from specialized factory settings to real-world deployment.
• Humanoid robots require sensor fusion across cameras, mmWave radar, tactile feedback sensors, and position encoders to make informed decisions.
• Advanced humanoid designs can exceed 50 degrees of freedom, requiring tight system-level integration of sensing, computing, communications, and motor control to synchronize movement reliably.

No one wants to fold laundry, but what if a robot could do it for you?

Enter humanoid robots. The humanoid market is estimated to reach US$5 trillion by 2050. Long viewed as futuristic, engineers have already built humanoid robots capable of operating in factory settings.

But that’s only a hint of their full potential. In order to achieve, semiconductors will be more critical than ever.

Traditionally, artificial intelligence (AI) has analyzed data to generate insights and support human decision-making.

“AI is becoming physical, and humanoid robots are one of the places where we can really see it,” said Giovanni Campanella, general manager for robotics and automation at TI.

Physical AI is the real-world manifestation of those AI models, which enable the humanoid to manipulate objects or navigate complex environments.

“Those capabilities are only possible because of advances in semiconductor technology,” said Giovanni.

We asked our experts to explain how semiconductor technologies could enable humanoid robots to move from specialized applications to scalable real-world systems, and what it will take to scale them for deployment.

Expanding the ability to perceive the world

Just as we use our senses to see and feel, engineers equip humanoid robots with sensors to perceive the surrounding environment.

For example, detecting objects requires reliable camera sensors for vision and spatial awareness, as well as tactile feedback sensors to differentiate tasks such as pulling a cable with torque versus opening a door.

But no single sensor can fully perceive the environment on its own.

“Millimeter-wave radar technology complements cameras and other sensors by providing robust perception in challenging lighting, dust, fog and occlusion conditions,” said German Aguirre, systems manager for robotics at TI. Meanwhile, position encoders give the robot feedback about where its limbs are.

“That’s why combining data from multiple sensing modalities is essential,” Giovanni said. “This design approach can unlock the potential of humanoid robots, expanding their use cases.”

Combining data from multiple sensors in order to create a more comprehensive understanding of a robot’s surroundings is known as sensor fusion.

“Engineers need sensor fusion to create humanoids that can execute more informed decisions,” German said, “like grasping differently sized objects, avoiding physical obstacles, and interacting safely with people.”

Adding motors for dexterity

Think about how many joints it takes to open and close your fist.

“Translating motion that may feel effortless for us into a robot requires motors, which must pair with sensors for the humanoid to complete safe and accurate movements,” Giovanni said.

Increasing dexterity requires more degrees of freedom – a term representing the number of joints in a humanoid robot’s hand, controlled by a motor – in order for them to perform complex tasks consistently.

“Engineers are putting more motors in their designs. The manufacturers we’re working with today are developing hands that could each have as many as 25 degrees of freedom,” German said. “Advanced humanoid designs can exceed 50 degrees of freedom, often requiring dozens of distributed motor-control nodes throughout the robot.”

Taking a system-level approach for scalability

As humanoid robots grow in complexity, coordinating an increasing number of motors with precise timing becomes critical.

“Scalability is becoming a greater challenge as the need for more motors increases,” Giovanni said.

How do engineers synchronize all of the motors across the robot’s entire body?

“A humanoid system is only as strong as its weakest subsystem,” German said. “Scalable humanoid platforms require tight integration of sensing, computing, communications and motor control.”

TI is enabling humanoids robots to scale with several technologies that work together:

• Real-time deterministic communications such as EtherCAT and industrial Ethernet technologies enable synchronized motion control across distributed actuators.
• Sensors capture the environment in which the humanoid operates.
• AI algorithms running on MCUs interpret the sensing data and make decisions.
• Motor control executes decisions through a continuous real-time feedback loop.

Increasing adaptability in human-centered environments

Humanoid robots operate in what’s known as structured and unstructured environments. In structured environments, robots operate in predictable conditions, but according to Giovanni, operating reliably in unstructured environments remains one of the industry’s biggest challenges.

“Achieving perception sensing in an unstructured environment requires fusing sensors such as radar, lidar and camera and running AI models so that the robot can detect, classify, localize and track objects under a wide range of operating conditions,” Giovanni said.

Ensuring safe human-machine interaction is another important consideration for moving humanoid robots into practical applications.

Radar can provide an additional sensing modality for obstacle detection and human presence awareness, helping improve overall system safety when combined with other sensors and functional safety architectures.

“This enables the robot to slow or stop when a human is nearby,” German said.

Real-time control microcontrollers often must meet functional safety standards and support safe communication. Our safety-certified power-management integrated circuits can power Safety Integrity Level 2-compliant mmWave radar sensors that enable a reliable and safe radar solution.

So, what’s next for humanoids?

“In the future, we’ll see better dexterity and fluid movement with more capable AI-driven decision-making powering these machines,” said German. ”We’ll feel more confident about safe interaction. Such progress will help shift robots from prototypes to real commercial deployments. The work TI is doing today is making that possible.”