As home robotics begins to step beyond research labs and factory floors into everyday environments, the technology powering them is under new scrutiny – particularly the chips at their core.
At this year’s Automatica trade show, several companies, including Neura Robotics (main image), unveiled new humanoid systems designed to operate in close proximity to people – in homes, care settings, and public spaces. While much attention has focused on the mechanical dexterity and AI capabilities of these robots, there’s another crucial layer that’s often overlooked: semiconductor reliability.
To explore this topic, Robotics & Automation News spoke with Bernd Lienhard, CEO of Vorago Technologies, a company known for its radiation-hardened semiconductor solutions.
Lienhard argues that as robots become more autonomous and human-facing, the risk of failure from environmental factors – including radiation-induced bit flips and electromagnetic interference – becomes non-trivial. Most consumer-grade chips aren’t designed to handle such conditions, especially with the precision and reliability needed for safe home robotics.
In this in-depth Q&A, Lienhard discusses the disconnect between the robotics and semiconductor sectors, how Vorago’s Hardsil technology addresses these challenges, and why the future of robotics depends on a new class of resilient, deterministic, and situationally aware chips.
Robotics and Automation News: Bridging the Gap: What’s the biggest disconnect between what the robotics industry currently needs from semiconductors and what the semiconductor industry is typically focused on delivering?
Bernd Lienhard: The biggest disconnect lies in optimization and specialization versus generalization. The semiconductor industry often prioritizes performance, cost, and power for broad markets like mobile, data centers, and automotive.
But the robotics industry needs more specialized characteristics – specifically, real-time processing, ruggedization, deterministic behavior, low latency, and fault tolerance.
Given the relatively small size of the robotics market, these needs often take a back seat in traditional chip roadmaps and design processes. Robotics systems must function reliably in dynamic, often unpredictable environments, and they require hardware that is purpose-built to handle those edge conditions.
For instance, if a household robot loses real-time sensor data while navigating a cluttered room, it might bump into furniture or tip over. That kind of failure points to a lack of deterministic processing and fault tolerance, something general-purpose chips aren’t designed to handle.
R&AN: Follow-up: Where does Vorago’s radiation-hardening technology fit into bridging that gap, particularly for the emerging home robotics market?
BL: Vorago’s Hardsil technology brings robust fault tolerance and environmental resilience to the table – qualities that are just beginning to be appreciated in home robotics.
While traditionally focused on space applications, our radiation-hardening innovation translates into greater uptime and safety for consumer devices that may be exposed to electrical noise, voltage spikes, or even terrestrial radiation.
As home robots become more autonomous and operate around humans, reliability and resilience become paramount. Vorago’s technology offers a path to commercial-grade robustness without the prohibitive cost and complexity of traditional radiation-hardened solutions.
R&AN: Beyond Radiation: What other critical, often overlooked, characteristics must semiconductors possess to make home robotics truly safe and scalable?
BL: There are several key criteria to keep in mind:
- Radiation resistance: As semiconductors are built on increasingly smaller nodes, they become more susceptible to terrestrial radiation. Even at ground level, stray particles can cause bit flips and system errors.
- Electromagnetic immunity: Devices must remain stable around sources of interference like Wi-Fi routers, microwave ovens, and power converters.
- Longevity: Consumer devices are expected to operate reliably for 5-10 years, but many semiconductors are not optimized for this level of durability.
- Security: As robots become more connected, chips must guard against cyber vulnerabilities – starting at the hardware level.
- Real-time response: Safety in motion control and decision-making depends on deterministic timing, not just raw compute speed.
Overall, chip designers must think beyond conventional metrics like speed and efficiency to incorporate environmental resilience, long lifecycle support, and native security features.
R&AN: Customization vs. General Purpose: How do chips specifically designed for AI and robotics differ from general-purpose chips (like those in a laptop)?
BL: Fundamentally, it’s about architecture, not just scale. Robotics and AI chips are optimized for parallelism, low latency, and the real-time handling of sensor fusion or neural network workloads.
General-purpose CPUs are designed for flexibility and broad software compatibility but often lack the deterministic timing and power efficiency needed for robotic workloads. A general-purpose chip might buffer sensor inputs and process them as batches, introducing lag.
That may work fine for editing a video on a laptop, but for a robotic assistant trying to avoid a toddler crawling on the floor, milliseconds of delay could lead to a safety-critical misinterpretation.
R&AN: Follow-up Analogy: Could you provide a simple analogy to explain this difference for a non-technical audience?
BL: Think of it like vehicles. A general-purpose chip is like a minivan: it’s versatile and good at many tasks but not exceptional at any single one. A robotics-specific chip is like a Formula 1 car, built for speed and precision on a racetrack.
It’s engineered for a specific environment and optimized for performance under strict conditions. You wouldn’t use one for the other’s job.
R&AN: Nvidia and Specialization: Is the robotics chip push a genuine divergence or a marketing play?
BL: It’s both. Nvidia’s underlying architectures are indeed versatile and powerful, and much of the differentiation comes through the software stack, I/O configuration, and optimization for real-time AI tasks.
What makes a robotics chip different isn’t just the silicon – it’s how the GPU or SoC handles sensor input, timing, and safety requirements. So yes, there’s a marketing element, but there’s also a real shift in architectural tuning for specific workloads like SLAM, vision processing, and control loops.
R&AN: The “Why” of Failure: What actually happens inside a semiconductor during radiation exposure, and how does Hardsil help?
BL: When a chip is exposed to radiation, high-energy particles penetrate the silicon and can cause single event upsets (SEUs), latch-ups, or even permanent degradation due to charge buildup in the chip’s structure. This can corrupt data, crash systems, or lead to unpredictable behavior – especially dangerous in safety-critical applications like home robotics.
Hardsil mitigates this by introducing a simple additional manufacturing step using standard equipment. This step subtly alters the silicon’s internal structure to make it less vulnerable to those stray particles. Rather than overhauling the entire design or adding complex protective hardware, Hardsil strengthens the silicon itself.
This approach enhances reliability without needing bulky shielding or redundant logic systems, making it especially useful for applications like home robotics, where space, weight, and cost are at a premium.
R&AN: Future of Home Robotics: How will semiconductor demands evolve as home robots become more autonomous and interactive?
BL: Future robots will need to operate with greater contextual awareness and real-time adaptability. This will require semiconductors that can process AI workloads locally, with ultra-low latency and high efficiency. Chips will need to support more sensor inputs, process them in parallel, and make decisions on the fly.
Additionally, fail-safe architectures and safety certifications will become baseline requirements as these devices interact more closely with people and navigate physical spaces.
A home robot could misinterpret a person or common object for open space because a radiation-induced bit flip corrupted its sensor data, leading to a collision. Ensuring resilience at the silicon level will be key to preventing these unpredictable, and potentially dangerous, malfunctions.
R&AN: Cost vs. Reliability: Is Vorago’s solution cost-prohibitive for the consumer market, or is it becoming more accessible?
BL: Traditionally, radiation-hardening was reserved for defense and space due to cost. But with Hardsil, we’ve closed much of that cost gap. By integrating our process into standard CMOS flows, we offer a compelling value proposition: significantly increased reliability with minimal cost overhead.
As chip demand grows in sensitive consumer environments, like home robotics, smart infrastructure, and automotive, our approach becomes not just feasible, but necessary.
R&AN: Innovation Drivers: What areas of semiconductor innovation will most impact robotics and AI in the next decade?
BL: Several areas come to mind:
- Edge AI architectures: Chips designed to efficiently run neural networks without needing to connect to the cloud.
- Heterogeneous integration: Combining different chiplets – such as AI cores, analog modules, and RF components – into one package to improve performance and reduce footprint.
- Advanced materials: Enhancing silicon for greater power efficiency or improved tolerance to radiation and harsh conditions.
- AI-driven chip design: Leveraging machine learning to optimize chip layouts and power usage more quickly than traditional methods.
- Security-hardened silicon: As robots handle personal and environmental data, built-in hardware-level encryption and trust zones will be critical.
Taken together, these innovations reflect a larger shift: moving from building chips that are fast and cheap to building chips that are situationally aware, resilient, and trusted. For robotics and AI to reach their full potential, especially in homes, hospitals, and public spaces, this evolution is completely necessary.
