Humanoid robots have long been the focus of science fiction, but today they are making their way into industrial environments thanks to the simultaneous maturing and convergence of multiple systems. Technology advances have driven the development of humanoid robots that have a wide range of movement and can perform demanding jobs around the clock without tiring. While currently representing a small share of all industrial robot deployments, the humanoid robot market is projected to grow rapidly over the next few years. In fact, estimates suggest the market could reach over $4 billion by 2030. This growth is being driven by factors such as labor shortages, falling costs, and the need for more flexible automation.
What sets humanoid robots apart from their industrial counterparts is their form and ability to carry out human-like tasks, which require a new level sensing, computing, power, and connectivity. Together, these technologies form a unified system that enables perception, decision-making, motion, and the sophisticated coordination of tasks across the robot’s body.
“The breakthrough isn’t one component — it’s a system-level integration,” said Thomas Schoepf, Vice President and CTO of Automation and Connected Living Sector, TE Connectivity.
Torque-dense motors and series elastic actuators provide precision control that enables humanoid robots to move and coordinate their actions. AI accelerators and high-speed networking provide integrated real-time perception, rather than relying on external computing. High-resolution force and tactile sensors anchor robots to their environment.
Humanoid robots must also deliver reliable performance in harsh conditions, where dirt, dust, humidity, heat, moisture, and constant vibration may be present, across extended operating cycles. Manufacturers have drawn best practices from many industries including electric vehicles (EV) where innovation in battery technology, thermal management, and sealing have been crucial to their success.
Why Humanoid Robots?
Deployed at scale during the 1970s and 1980s, industrial robots have since been workhorses of industry. However, they are functionally rigid. Redeploying them for new activities requires weeks of redesigning processes and the environment.
Humanoid robots, on the other hand, are software-defined performance engines instead of task-specific machines. They can scale stairs, use elevators, and learn and repeat tasks, which enable them to succeed in both current industrial environments as well as those built for humans. That means humanoid robots can be used in a wide range of scenarios such as retail and hospitality service, healthcare and eldercare assistance, and general-purpose labor.
“A huge advantage that humanoid robots provide is that they can operate in environments which are already built for humans. We can use all the infrastructure and investments that are already in place,” said Thomas.
While costs limit large-scale deployment at present, they are projected to fall sharply. For example, a humanoid robot that cost $158.4K in 2024 is slated to cost only $38.1K in 2030, putting investment almost on par with projected industrial robot costs at $29.5K while significantly increasing operational flexibility.
The Engineering Challenges of Designing Motion-Dense Systems
Humanoid robots typically use a hybrid architecture that combines distributed low-level controllers for real-time joint and sensor control with centralized high-level intelligence for perception and planning. As Thomas explained, “A humanoid robot is best understood as a distributed system coordinated by centralized intelligence.” This approach reduces latency, improves scalability across many joints, and enhances fault isolation. These architectural advantages introduce a new set of engineering constraints that accompany high degrees of freedom and dense electromechanical integration.
Designing humanoid robots for a wide range of motion experience is an extremely complex process. “With 30 to 50 degrees of freedom, the complexity scales quickly. The power distribution becomes multi-rail and high current, and the data traffic increases significantly,” added Thomas.
Robotic joints are powered by electric actuators that integrate elements such as brushless DC motors, harmonic drives, cycloidal gear systems, torque sensors, motor controllers, and position encoders that enable movement and balance. This requires high-frequency feedback loops, predictive balance algorithms, and real-time fault detection to detect the position of every element of the humanoid robot, preserve stability and control across all joints.
Engineers use high-flex cables to route connectivity through moving joints and minimize strain, torsion, and fatigue. With a human-sized form factor, they also use high-density packaging for robot hands and feet to mitigate space constraints.
Other technologies that preserve space include smaller sensing units with multiple modalities and hybrid connectors that package power, signal, and data into a single unit.
The humanoids’ motor drives introduce interference risk for sensors and high-speed data transmission which must be mitigated.
“There’s a lot of careful engineering that goes into designing reliable high-speed connectivity in a space-constrained, high interference environment,” said Thomas. Engineers carefully design interconnect systems for humanoid robots, using shielded cables, differential signaling, EMI filters, and grounding strategies. They may also isolate high-current motor drives and switching electronics from signals to minimize EMI interference.
Another priority is balancing miniaturization and serviceability. Designers use dense packaging in robot joints and fingers, but smaller systems can also present ongoing service challenges. Robot design platforms should enable plug-and-play limb replacement if something goes wrong, as well as provide redundant sensing, environmental sealing to meet standards, health monitoring systems, and predictive diagnostics to maximize uptime.
“We need connectors that are small enough and reliable enough to work in a challenging environment, but also able to be disconnected, replaced, or upgraded within a very constrained space,” said Thomas.
A central electronic “brain” coordinates the humanoid robot’s balance, perception, and task planning, with increasing use of AI to improve performance can capability. Local joint controllers manage local motor loops and are connected by high-speed communication buses that connect subsystems, enabling synchronized motion across dozens of actuators.
Connectivity functions as the robot’s internal nervous system. This internal network must support deterministic communication across distributed subsystems using industrial protocols such as real-time Ethernet. It must provide Gigabit-plus data rates, low latency, and reliable operations in space-constrained, motion-intensive environments.
“That requires very high-speed networking in a very tough environment. We’re talking about gigabit-rate networking within very complicated, multi-articulate joints,” said Thomas.
Understanding Operational Capabilities and Constraints
Humanoid robots use sensor fusion to combine data from different sources such as vision systems, inertial measurement units (IMUs), force sensors, and joint encoders, and create a unified understanding of their environment and condition. They use this integrated insight to move, balance, manipulate objects, and interact safely with their surrounding environment.
“An important part of sensor fusion is using discrete, time-stamped sensor streams and bringing it together with high-reliability, timestamped information to enable humanoid robots to make a decision about what to do in their environment,” added Thomas.
Additionally, while humanoid robots don’t fatigue, they still experience design and operational constraints. They’re typically powered by 48-75V battery systems that must balance energy density, weight distribution, and thermal performance. In addition, they need to be charged on an ongoing basis.
Some emerging design approaches include providing automated docking stations for battery swapping. Eventually, robots may be able to swap out their own batteries, enabling continuous operations.
Developing Scalable Humanoid Platforms
Current barriers to scaling this technology include the current high cost of humanoid robots, thermal constraints, and weights which are two to three times that of a human. Many times existing brownfield infrastructure can’t support that weight. As time goes on, designers will look to use novel materials, including composites, and continue to miniaturize components to reduce humanoid robot weight.
To build for scale, designers will opt for standardized modular architectures, higher internal voltages to reduce cable weight and create efficiencies, and distributed edge AI technology. Sensor density will continue to increase, placing additional pressure on synchronization.
Component manufacturers can support continued innovation by working side by side with manufacturers to understand their requirements, design for standardization and interoperability, and provide a wide range of sensors and interconnects to support robots’ power distribution, signal and data processing requirements, while protecting operations from EMI interference.
As humanoid robots evolve from experimental systems to industrial platforms, their success will depend less on any individual technological breakthrough and more on how effectively engineers integrate connectivity, sensing, power, and computing into a cohesive architecture. Interconnect design becomes a critical foundation to driving performance and enabling reliability, scalability, and the long-term viability of scale implementations.
This article was written by Davy Brown, Vice President & CTO, Transportation Solutions, TE Connectivity (Berwy, PA). For more information, visit here .
