New lidar platforms promise safer, more efficient, and more autonomous industrial systems

From factory floors and fulfillment centers to distribution hubs, automation is accelerating. Robots, forklifts, and mobile platforms now move materials, inspect products, and coordinate with human workers, all in increasingly dynamic environments.

This shift has created a surge in demand for advanced sensing: technologies that allow machines to perceive their surroundings with the accuracy, reliability, and contextual awareness of a trained human operator.

The global warehouse automation market is expected to grow from about $30 billion in 2025 to more than $60 billion by 2030, with robotics leading the charge at double-digit annual growth rates. The challenge is that many of today’s sensors—cameras, radar, and conventional lidar—can’t keep pace with the complexity or scale of industrial autonomy.

To make “autonomous everything” possible in manufacturing and logistics, sensing technology must become smaller, more capable, and dramatically more affordable.

Why sensing matters more than ever

Vision systems have been essential for automating repetitive tasks, but they often fail where precision, speed, and environmental variability intersect.

• Cameras struggle with glare, shadows, and low-light conditions.
• Time-of-flight (ToF) sensors deliver useful depth maps but lose range precision over distance and under bright lighting.
• Conventional lidars but remain limited in precision, expensive, and difficult to scale for high-volume deployments.

Industrial automation environments add further complexity: shiny shrink wrap, reflective metal pallets, dust, and vibration can all interfere with sensing performance. Robots working side by side must also avoid cross-talk interference when dozens of sensors operate simultaneously.

The result is a growing demand for a new class of 3D sensing—one that combines sub-centimeter accuracy, compact integration, and immunity to lighting or environmental noise.

The future of automation depends on perception that is as scalable as it is precise. That’s where chip-based FMCW lidar makes the leap from lab to warehouse.

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FMCW lidar: Measuring distance and motion together

One of the most promising breakthroughs is frequency modulated continuous wave (FMCW) lidar, a technology that uses the same ranging principle as radar, applied to light, bringing an order-of-magnitude higher resolution.

Unlike traditional ToF lidar, which measures the return time of laser pulses, FMCW lidar emits a continuous beam whose frequency is steadily “chirped.” When the reflected light returns, it’s mixed coherently with a copy of the transmitted signal. The resulting beat frequency reveals both the distance to the object and its relative velocity.

That dual measurement unlocks several critical advantages for industrial automation:

• Range and velocity in one scan, eliminating multi-frame calculations
• Sunlight and ambient light immunity, since the system detects frequency, not brightness
• Freedom from cross-talk, even in dense multi-robot environments
• High signal-to-noise ratio, preserving accuracy through fog, dust, or glare

In practical terms, FMCW lidar can deliver a detailed multi-dimensional picture—depth, reflectivity, and motion—allowing machines to see not just where objects are, but how they’re moving.

Silicon photonics: The key to scalable lidar

While FMCW delivers superior sensing physics, silicon photonics delivers scalability.

By integrating the light emission, beam steering, and coherent detection onto a single photonic chip, silicon photonics eliminate the need for bulky optics, complex alignment, and moving parts. The process uses mature semiconductor foundries—the same kind that produce datacom components—allowing lidar sensors to be built at wafer scale.

The results can include:

• Miniaturization: Sensors small enough to embed in robot arms or autonomous mobile robots (AMRs).
• Reliability: Fewer moving parts to wear out or drift.
• Affordability: Production costs drop by orders of magnitude through high-volume manufacturing.
• Consistency: Factory-calibrated chips ensure uniform performance across fleets.

Voyant’s integrated FMCW architecture exemplifies this trend, achieving “lidar-on-a-chip” integration with both emitter and receiver on the same die. That design makes advanced 3D sensing as manufacturable as a processor or camera sensor, bringing it within reach of scale deployment leveraging the exponential capability of silicon industry.

Industrial use cases: Where precision meets productivity

FMCW lidar’s ability to deliver dense 3D data and velocity feedback in real time makes it suitable for many core industrial automation applications. Below are several use cases where this type of technology delivers tangible benefits.

1. Pallet handling and forklift guidance

In warehouses and distribution centers, pallet engagement remains one of the most precision-critical operations. Autonomous forklifts and pallet movers must align forks with narrow pallet entry slots and compensate for irregular loads.

Compact FMCW lidar modules can be mounted on the mast or chassis, providing wide-field of view, high-resolution 3D data, Sub centimeters precision and velocity tracking.

The system accurately measures both the robot’s approach speed and the pallet’s position, even under plastic wrap or glossy coatings. The result: fewer collisions, faster loading cycles, and reduced manual intervention, leading to higher throughput and safety.

2. Robotic picking and object manipulation

In e-commerce and fulfillment centers, robotic arms are increasingly responsible for picking, sorting, and transferring items between conveyors or bins. However, vision-only systems often struggle with object orientation, occlusion, and reflective packaging.

Chip-scale lidar can be integrated directly into a robot’s wrist or end effector, enabling sub-centimeter mapping of items in 3D space. This allows arms to:

• Plan optimal grasp points and trajectories in real time.
• Recognize and handle objects of varying shapes and materials.
• Operate with faster cycle times and fewer mispicks.

Because the lidar module is small and self-contained, it can be installed in places where bulky sensors can’t fit — paving the way for more dexterous, scalable robot deployments.

3. Mobile platform navigation and localization

AMRs and automated guided vehicles (AGVs) must navigate vast facilities where lighting conditions, surfaces, and obstacles vary constantly.

Traditional navigation relies on visual simultaneous localization and mapping (vSLAM), wheel odometry, or external markers — all prone to drift or error in feature-poor environments. FMCW lidar can provide ego-motion estimation through Doppler-based velocity sensing, letting robots measure their own movement directly against the environment.

This improves localization accuracy, reduces dependence on external sensors like GPS, and maintains robust mapping performance across indoor/outdoor boundaries. For operators, it means fewer navigation errors, higher uptime, and lower maintenance costs.

4. Safety, collaboration, and human detection

In collaborative environments, safety is paramount. Machines must not only detect people but also interpret their movement. FMCW lidar’s velocity-awareness enables predictive collision avoidance — distinguishing between a stationary obstacle and a moving human or vehicle in a single frame.

This allows robots to slow or stop before a hazard occurs. The result is smoother workflows where humans and robots can share space without costly safety cages or sensor redundancies.

5. Mixed environment logistics and yard autonomy

Many logistics facilities now extend outdoors, where AMRs and forklifts move between indoor warehouses and open-air yards. FMCW lidar operates reliably in these transitions, unaffected by sunlight or glare that would saturate camera or ToF systems.

By maintaining precise range and velocity data under any lighting, these efficient and flexible sensors can enable around-the-clock operation — critical for high-volume logistics and manufacturing environments where uptime is non-negotiable.

Why the timing is right for FMCW lidar

The industrial automation sector is evolving from large, fixed installations toward modular, scalable robotics. These are systems that can be deployed flexibly in existing facilities, not just new builds. That shift demands sensors that are smaller, cheaper, and more integrated.

A silicon-photonics-based FMCW lidar directly addresses that transition:

• Compact form factor for easy integration into AMRs, robot arms, and forklifts.
• 10× lower cost than comparable high-performance lidar units.
• Wafer-scale manufacturing for high-volume consistency.
• Sub-centimeter precision and high immunity to interference or ambient light.

Physical AI: The convergence of sensing and intelligence

Artificial intelligence allows machines to plan, reason, and optimize. But in physical environments, intelligence is useless without perception. This intersection of sensing and AI is the next great frontier in automation.

In this new paradigm, sensors act as the eyes and ears of autonomous systems, enabling real-time spatial awareness that fuels machine learning and decision-making. To make this widespread, sensing must follow the same scalability path as computing, moving from bespoke hardware to integrated chips produced in the millions.

That’s exactly what silicon photonics and FMCW lidar make possible: perception that scales like semiconductors.

Latest lidar can transform industrial economics

Affordable, scalable lidar changes the equation for industrial autonomy. Robots and vehicles equipped with compact, high-fidelity sensors can operate safely alongside humans, adapt dynamically to new layouts, and deliver faster return on investment (ROI) through fewer errors and simpler integration.

For system integrators, it means more flexible deployment architectures. For operators, it means reliability and cost-efficiency without sacrificing performance. For the market as a whole, it signals the transition from automation as a project to autonomy as a platform—a foundation for the next wave of industrial productivity.

As warehouses, factories, and supply chains continue to evolve toward full autonomy, the machines that can see — and understand — the world most precisely will define the leaders of the Physical AI Era.

About the author

Clément Nouvel is the CEO of New York-based Voyant Photonics, a leader in silicon photonics-based lidar. Before joining Voyant, he spent nearly a decade leading global lidar programs at Valeo, bringing some of the world’s first automotive-grade lidar systems into mass production.

Prior to that, Nouvel spent 12 years at Renault Samsung Motors. He holds Masters in Science degrees from Ecole Polytechnique and CentraleSuplec, and an MBA from Insead. Nouvel said he is passionate about advancing scalable sensing technologies to enable the physical AI revolution.

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