Co-Designing On-Device Inference, Real-Time Control and Trusted Operation
Humanoid robots and embodied AI must combine perception, model inference, motion control and data exchange within tight power and space constraints. Inference efficiency, real-time control, and protection of models and devices are interconnected challenges for chip and system designers.
Foresemi provides on-device AI inference, real-time mathematical acceleration, cryptographic security and data-reliability IP for robotic SoCs and control MCUs, supporting a coherent architecture from specialized computing to trusted operation.
On-Device Inference & Model Protection
Real-Time Motion Control
Trusted Operation & Software Security
Humanoid robots move and interact with people. Cameras, microphones and activity records can capture private home or workplace environments, including people who do not operate the device. Development teams must determine which data is necessary, what can remain on-device, what must be uploaded, who may access it and how long it is retained. Encrypting an upload link does not replace controls on data collection and use.
Embodied AI connects perception and decisions to physical action. Forged commands, disrupted sensing or tampered models can cause physical harm or property damage, not merely incorrect output. Remote operation, model updates and actuator control each need explicit authorization boundaries and verifiable safe responses to abnormal commands or lost connections.
Security means more than preventing a takeover. Operators need to understand when autonomous decisions can be trusted and when human intervention is required. Define those boundaries early and retain essential command, firmware-version and event records so that model decisions, software faults, operator errors and external interference can be distinguished, with clear responsibilities across development, integration and operation.
Products processing personal information need to assess the applicability of rules such as China’s Personal Information Protection Law and the GDPR against their target markets and actual data flows. Relevant connected products for the EU also need to consider the Cyber Resilience Act (CRA), including security-by-design, third-party components and vulnerability handling during the support period. Code provenance, component versions and patch records belong in ongoing development management, not just a pre-shipment check.
CIMEURA® uses SRAM-based digital compute-in-memory to reduce inference data movement and address energy-efficiency needs in robotic on-device and edge computing.
DH-TMU™ accelerates CORDIC mathematics and FOC control calculations, offloading trigonometric functions, coordinate transforms and control-loop computation to preserve main-core resources for real-time tasks.
CryptICE™ compresses, encrypts and loads model weights, reducing weight-transfer overhead at a given DDR bandwidth and limiting plaintext exposure of off-chip model assets.
CryptHSM® provides secure boot and updates, key management and cryptographic services; DesignHub™ cryptographic IP supports data protection and authentication, while DH-ECC adds error correction and detection for memory and data paths.
Share your target SoC or MCU, inference and control tasks, power and bandwidth targets, and model and device security requirements. We will arrange a technical discussion.
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