TDK and Microchip Technology partner to enable sensor networks for robotics

TDK and Microchip have demonstrated a distributed sensor-node platform engineered for advanced robotic systems and humanoid platforms. Showcased at electronica, held November 10 to 13, 2026, in Munich, Germany, the architecture integrates InvenSense inertial sensing with single-pair Ethernet connectivity and digital signal controllers to deliver localized edge processing directly at physical robotic joints and articulation nodes.

Cabling Weight and Bandwidth Bottlenecks in Humanoid Articulation
Next-generation bipedal and humanoid robots deploy 100 or more discrete sensing instruments to manage motor actuation, multi-axis force-torque feedback, environmental perception, and closed-loop joint stabilization. Routeing analog or point-to-point digital wiring from dozens of distributed sensors back to a centralized host processor introduces substantial wiring harness weight, mechanical fatigue across rotating joints, and high electrical noise susceptibility. Centralized compute architectures also experience processing bottlenecks and communication latency when handling high-frequency raw telemetry alongside perception and path-planning workloads. Mitigating these mechanical and computational loads requires distributing deterministic data processing to the physical sensor location over lightweight networking infrastructure.

Hardware Architecture and Single-Pair Ethernet Integration
The demonstration platform interfaces micro-electromechanical systems from TDK’s InvenSense group with Microchip's processing and physical layer components. The reference hardware incorporates the Microchip dsPIC33A digital signal controller, LAN8651/LAN8679 10BASE-T1S single-pair Ethernet transceivers, a TDK InvenSense SmartMotion ICM-42688-P six-axis inertial measurement unit, and a standardized MikroE expansion interface.

The dsPIC33A digital signal controller integrates a 200 MHz 32-bit core, hardware digital signal processing acceleration, a double-precision floating-point unit, high-speed analog-to-digital converters, and high-resolution pulse-width modulation modules. The onboard controller manages local data acquisition, sensor filtering, and signal conditioning. By utilizing 10BASE-T1S multi-drop Ethernet topology, the architecture multiplexes multiple nodes onto a single balanced pair of conductors, replacing heavy multi-conductor cabling bundles with an integrated multidrop network.

Edge Sensor Fusion and Real-Time Kinematics
The InvenSense ICM-42688-P packages a three-axis gyroscope and a three-axis accelerometer, providing high-precision proprioceptive telemetry for joint monitoring, motion stabilization, and structural vibration tracking.

At the node level, the dsPIC33A executes edge machine learning models, including real-time gesture classification and vibration diagnostics, directly from raw kinematic data. The controller performs localized sensor fusion algorithms, calculating angular orientation and torque metrics before packaging structured diagnostic metadata for transmission to the central robot controller.

Expansion capabilities via the MikroE interface allow developers to connect secondary sensing arrays, including the InvenSense PositionSense nine-axis platform for absolute spatial orientation.

System Scalability and Dynamic Performance
Decentralizing signal conditioning and machine learning inference directly to individual articulation joints offloads critical processing cycles from central host compute units. The combination of localized digital signal processing and single-pair Ethernet reduces harness volume, minimizes control loop latency, and provides a scalable hardware foundation for continuous motor control in complex humanoid robotics.

Edited by Romila DSilva, Induportals Editor, with AI assistance.