On August 27, 2026 in Computing, Robotics by Microchip Technology
Robots are proliferating across a wide range of applications, and many are tailored closely to the task they perform. Wheeled robots, for example, can handle goods in warehouses, while industrial robotic arms can weld metal components together. Meanwhile, humanoid robots are gaining traction because of their versatility. They offer the flexibility to perform a variety of tasks while operating autonomously in dynamic environments and mimicking human motion.
To perform their assigned tasks safely while maintaining their own stability around humans, humanoid robots require high-performance hardware and software capable of managing the many sensors and motors that enable them to perceive and act. Field-programmable gate arrays (FPGAs) are well-suited to serve as the brains in humanoid robotic applications (Figure 1). FPGAs can flexibly and deterministically process multiple sensor inputs while controlling the dozens of motors that give robots human-like dexterity.
This blog examines how FPGAs support sensor processing and motor control in autonomous humanoid robots.
Perceiving the Environment
Humanoid robots use a variety of sensors to map their work environment and determine how to complete their assigned tasks. Like other robotic systems, humanoid robots may rely on LiDAR for 3D mapping, embedded vision sensors for object recognition, ultrasound for collision avoidance, and radar. Radar is particularly valuable because it can operate reliably in adverse weather and low-light conditions while simultaneously measuring a target's distance and velocity.[1]
While these sensor modalities apply to robots in general, humanoid robots face additional challenges. For example, a wheeled warehouse robot can navigate to a programmed location and then lock its wheels, creating a stable platform for its next task, such as retrieving an item scheduled for shipment. By comparison, a humanoid robot must constantly maintain whole-body awareness. To do so, it relies on proprioceptive sensors to monitor body orientation, finger pressure, joint rotation, limb position, and foot placement. These sensors can include inertial measurement units (IMUs) that measure acceleration and angular velocity, force and torque sensors that monitor weight distribution on each foot, and rotary encoders that track joint angle and velocity.
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