Presented by Analog Devices Inc.
(Image courtesy of Analog Devices Inc.)
Not long ago, simply getting a robot to travel from point A to point B was enough for most site owners. Those days are gone. Modern robots must now move faster, handle ever‑changing surroundings, and navigate around an increasing number of obstacles. Under these tougher requirements, vision systems have become essential for navigation and spatial awareness.
“The biggest challenge is no longer just the image quality itself,” notes Stephen Liu, robotics lead at embedded‑systems specialist Advantech. “It’s system‑level orchestration. As sensor counts grow, robotic OEMs must juggle bandwidth, latency, synchronization, and compute all at once.”
These platforms move vast amounts of real‑time data; if the interfaces can’t keep up with throughput, perception turns unreliable. Sensor fusion is equally demanding—even a few milliseconds of timing drift among cameras, lidars, and IMUs can undermine navigation accuracy.
“Robots don’t just see; they have to decide and act on the spot,” Liu points out. “That demands tight coordination between the GPU, MPUs, and a real‑time operating system in order to deliver deterministic performance.”
Harsh environments add yet another layer of difficulty. Robots may need to function reliably through vibration, dust, moisture, and temperature extremes, all while fitting cables into tight, compact designs.
“When cable lengths grow, connectors come under extra strain and electrostatic‑discharge (ESD) interference becomes a much bigger concern,” Liu explains. “We need rock‑solid synchronized vision inputs and long‑distance video transmission, especially in ruggedized settings.”
One technology rapidly gaining traction across the robotics industry to meet these vision‑architecture needs is GMSL.
“GMSL is a game changer for multi‑camera robotics,” Liu says. “High‑resolution video, control signals, and synchronization are all carried over a single, lightweight cable with very high reliability and minimal latency. This dramatically cuts cabling complexity, strengthens EMI resistance, and enables precise hardware‑level time‑stamping. From an integration standpoint, it simplifies system design as well.”
Similar architectures have long been deployed in automotive systems; now, as the GMSL ecosystem has matured, those design practices are making their way into robotics.
“The transition feels very natural,” Liu observes. “Automotive systems such as ADAS and autonomous driving already solved many of the same problems robotics faces today—multiple synchronized cameras, lengthy cable runs, demanding operating conditions. Robots operating in warehouses, farms, or urban areas are, in effect, vehicles: they move quickly, run for extended periods, and can’t afford perception lapses. By leveraging automotive‑grade GMSL technology, robotics teams gain proven robustness, deterministic latency, and scalability.”
Today’s deployments go well beyond proof‑of‑concept (POC) projects; many production robots already depend on GMSL. Roughly a third of the robotic opportunities Liu oversees are either using or evaluating GMSL cameras. After gaining momentum in warehouse autonomous mobile robots (AMRs), the technology is spreading to platforms such as humanoid robots and picking stations, with accelerating adoption in agriculture and certain healthcare applications. In construction environments, robotic solutions are enhancing safety and efficiency around heavy machinery.
ADI already offers a rich GMSL ecosystem that compresses the journey from concept to deployment. Instead of spending months wrestling with low‑level camera integration and driver deployment, teams can begin with pre‑validated camera modules, adapters, board‑support packages (BSPs), and ROS‑ready platforms. The result is faster prototyping, reduced integration risk, and a smoother progression from POCs to mass production.
“Robotics developers can concentrate on what truly sets them apart—AI models, autonomy logic, application software, and deployment strategies—rather than reinventing the sensing infrastructure,” Liu remarks.
For startups, incubators, and other innovators, speed and agility matter more than ever. In a robotics market where time‑to‑market often feels like a sprint, strategic partnerships and turnkey solutions offer a clear edge; without them, many developers would struggle to deliver solutions on schedule.
“We’re democratizing GMSL camera technology for small‑ and medium‑sized robotics companies that operate in low‑volume, high‑mix production environments,” Liu says.
Compute is another piece of the puzzle. Developers frequently need to handle low‑level configuration and coding, along with various AI SDKs and development tools, to squeeze out peak performance. This work demands expertise in both cameras and computing platforms. Advantech is helping customers integrate GMSL cameras across a range of platforms—from Intel and Qualcomm to NVIDIA—where the details differ from one system to the next.
“We believe ADI and Advantech can play a bigger role in harmonizing and accelerating those computing‑and‑camera integrations,” Liu states. “Ultimately, customers expect someone to deliver a working, ready‑to‑use system that combines both the computer and the camera.”
To learn more about ADI’s GMSL ecosystem, visit analog.com/gigabit‑multimedia‑serial‑link.
To learn more about Advantech’s solutions, visit advantech.com/gmslcamera‑afe‑asr.
