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Building high performance robotic vision with GMSL

Arrow Times07 Oct 2026
Illustration of an Advanced Driver Assistance System (ADAS) around a top-view car.
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Robotic systems increasingly rely on vision to perceive and interact with their environment, creating growing demands for high speed, low latency data links. Gigabit Multimedia Serial Link (GMSL™) offers a promising solution by transmitting video, control signals, and power over a single cable with high reliability. This article examines how cameras are deployed in robotics, the connectivity challenges they face, and how ADI's GMSL serializer solutions can enable scalable, robust, and performance-driven robotic platforms.

GMSL enables machine vision capabilities in robotic systems

Robotic systems increasingly depend on advanced machine vision to perceive, navigate, and interact with their environment. As both the number and resolution of cameras grow, the demand for high speed, low latency links capable of transmitting and aggregating real-time video data has never been greater.
 
Gigabit Multimedia Serial Link (GMSL™), originally developed for automotive applications, is emerging as a powerful and efficient solution for robotic systems. GMSL transmits high speed video data, bidirectional control signals, and power over a single cable, offering long cable reach, deterministic microsecond-level latency with an extremely low bit error rate (BER). It simplifies the wiring harness and reduces the total solution footprint, ideal for vision-centric robots operating in dynamic and often harsh environments.
 
Cameras are at the heart of modern robotic perception, enabling machines to understand and respond to their environment in real time. Whether it's a warehouse robot navigating aisles, a robotic arm sorting packages, or a service robot interacting with people, vision systems are critical for autonomy, automation, and interaction. These cameras are not only diverse in function but also in form -- mounted on different parts of the robot depending on the task and tailored to the physical and operational constraints of the platform.
 
In autonomous robotics, cameras serve as the eyes of the machine, allowing it to perceive its surroundings, avoid obstacles, and localize itself within an environment. For mobile robots, such as delivery robots, warehouse shuttles, or agricultural rovers, this often involves a combination of wide field-of-view cameras placed at the corners or edges of the robot. These surround-view systems provide 360° awareness, helping the robot navigate complex spaces without collisions.

Diagram illustrates an automotive sensor fusion architecture connecting multiple sensors to system-on-chips. Radar, surround view RGB camera, forward or rear-facing main camera, depth camera, application-specific camera, and 3D lidar feed into GMSL deserializers. The deserialized data is then routed to autonomous SoC, automation SoC, human interaction SoC, and functional safety replication modules. The layout uses simple labeled boxes and arrows to show data flow between sensing and processing components.

Example of a multimodal robotic vision system enabled by GMSL

Vision systems help robots achieve high-precision task automation

In industrial automation, vision systems help robots perform repetitive or precision tasks with speed and consistency. Here, the camera might be mounted on a robotic arm -- right next to a gripper or end-effector -- and the system can visually inspect, locate, and manipulate objects with high accuracy. This is especially important in pick-and-place operations, where identifying the exact position and orientation of a part or package is essential.
 
Some inspection robots, especially those used in infrastructure, utilities, or heavy industry, carry zoom-capable cameras mounted on masts or articulated arms. These allow them to capture high resolution imagery of weld seams, cable trays, or pipe joints -- tasks that would be dangerous or time-consuming for humans to perform manually.
 
Cameras also play a central role in how robots engage with humans. In collaborative manufacturing, healthcare, or service industries, robots need to understand gestures, recognize faces, and maintain a sense of social presence. Vision systems make this possible.
 
Humanoid and service robots often have cameras embedded in their head or chest, mimicking the human line of sight to enable natural interaction. These cameras help the robot interpret facial expressions, maintain eye contact, or follow a person's gaze. Some systems use depth cameras or fisheye lenses to track body movement or detect when a person enters a shared workspace.
 
In collaborative robot (cobot) scenarios, where humans and machines work side by side, machine vision is used to ensure safety and responsiveness. The robot may watch for approaching limbs or tools, adjusting its behavior to avoid collisions or pause work if someone gets too close.
 
As vision systems become the backbone of robotic intelligence, opportunity and complexity grow in parallel. High performance cameras unlock powerful capabilities -- enabling real-time perception, precise manipulation, and safer human interaction -- but they also place growing demands on system architecture. It's no longer just about moving large volumes of video data quickly. Many of today's robots must make split-second decisions based on multimodal sensor input, all while operating within tight mechanical envelopes, managing power constraints, avoiding electromagnetic interference (EMI), and maintaining strict functional safety in close proximity to people.

Chart compares data rates for various automotive sensing devices including radar, 3D LIDAR point cloud, ToF camera, stereo camera, front-facing camera, and surround view camera. Horizontal blue bars show data rate values along an axis from 0 to 12 Gbps. Vertical dashed lines mark GMSL2 3 Gbps, GMSL2 6 Gbps, and GMSL3 12 Gbps thresholds. The visualization highlights how different camera and sensor types approach or exceed these GMSL bandwidth levels.

Sensor bandwidth ranges and GMSL capabilities

Solving the challenges of robotic vision systems with GMSL

GMSL is uniquely positioned to meet the demands of modern robotic systems. The combination of bandwidth, robustness, and integration flexibility makes it well suited for sensor-rich platforms operating in dynamic, mission-critical environments. For example, GMSL supports high data rate and low latency technology, and the GMSL2™ and GMSL3™ product families support forward-channel (video path) data rates of 3 Gbps, 6 Gbps, and 12 Gbps, covering a wide range of robotic vision use cases. These flexible link rates allow system designers to optimize for resolution, frame rate, sensor type, and processing requirements.
 
A 3 Gbps link is sufficient for most surround view cameras using 2 MP to 3 MP rolling shutter sensors at 60 frames per second (FPS). It also supports other common sensing modalities, such as ToF sensors, light detection and ranging (LiDAR) units with point-cloud outputs, and radar sensors transmitting detection data or compressed image-like returns.
 
The 6 Gbps mode is typically used for the robot's main forward-facing camera, where higher resolution sensors (usually 8 MP or more) are required for object detection, semantic understanding, or sign recognition. This data rate also supports ToF sensors with raw output, or stereo vision systems that either stream raw output from two image sensors or output processed point cloud stream from an integrated image signal processor (ISP). Many commercially available stereo cameras today rely on this data rate for high frame-rate performance.
 
At the high end, 12 Gbps links enable support for 12 MP or higher resolution cameras used in specialized robotic applications that demand advanced object classification, scene segmentation, or long-range perception. Interestingly, even some low resolution global shutter sensors require higher speed links to reduce readout time and avoid motion artifacts during fast capture cycles, which is critical in dynamic or high speed environments.
 
Because GMSL uses frequency-domain duplexing to separate the forward (video and control) and reverse (control) channels, it enables bidirectional communication with low and deterministic latency, without the risk of data collisions. Across all link rates, GMSL maintains impressively low latency: the added delay from the input of a GMSL serializer to the output of a deserializer typically falls in the lower tens of microseconds -- negligible for most real-time robotic vision systems. The deterministic reverse-channel latency enables precise hardware triggering from the host to the camera -- critical for synchronized image capture across multiple sensors, as well as for time-sensitive, event-driven frame triggering in complex robotic workflows. Achieving this level of timing precision with USB or Ethernet cameras typically requires the addition of a separate hardware trigger line, increasing system complexity and cabling overhead.

Diagram illustrates a CMOS image sensor connected within an electronic imaging system. The sensor interfaces via MIPI CSI-2, I2C, FSYNC/RST/PWDN, and MCLK signals to a MAX96717 device. Additional blocks include nonvolatile memory (NVM), a power management IC, and a PoC filter feeding the circuitry. The layout uses a blue background with simple line connections and labeled components to explain the signal and power architecture.

Typical GMSL camera architecture using MAX96717

Highly integrated GMSL serializers simplify cable and connector infrastructure routing

One of the key value propositions of GMSL is its ability to reduce cable and connector infrastructure. GMSL itself is a full-duplex link, and most GMSL cameras utilize the power-over-coax (PoC) feature, allowing video data, bidirectional control signals, and power to be transmitted over a single thin coaxial cable. This significantly simplifies wiring, reduces the overall weight and bulk of cable harnesses, and eases mechanical routing in compact or articulated robotic platforms.
 
In addition, the GMSL serializer is a highly integrated device that combines the video interface (for example, MIPI-CSI) and the GMSL PHY into a single chip. The power consumption of the GMSL serializer, typically around 260 mW in 6 Gbps mode, is favorably low compared to alternative technologies with similar data throughput. All these features will translate to smaller board areas, reduced thermal management requirements (often eliminating the need for bulky heatsinks), and greater overall system efficiency, particularly for battery-powered robots.
 
GMSL deserializers are available in multiple configurations, supporting one, two, or four input links, allowing flexible sensor aggregation architectures. This enables designers to connect multiple cameras or sensor modules to a single processing unit without additional switching or external muxing, which is especially useful in multicamera robotics systems.
 
In addition to the multiple inputs, GMSL SERDES also supports advanced features to manage and route data intelligently across the system. These include I2C and GPIO broadcasting for simultaneous sensor configuration and frame synchronization, and I2C address aliasing to avoid I2C address conflict in passthrough mode. In addition, GMSL SERDES also supports virtual channel reassignment, allowing multiple video streams to be mapped cleanly into the frame buffer inside the systems on chip (SoCs), and features video stream duplication and virtual channel filtering, enabling selected video data to be delivered to multiple SoCs. For example, to support both automation and interaction pipelines from the same camera feed or to support redundant processing paths for enhanced functional safety.
 
The MAX96717 from ADI is a CSI-2 to GMSL2 serializer. The MAX96717 receives video on an MIPI CSI-2 interface and outputs it on a GMSL2 serial link transceiver. Simultaneously, it sends and receives bidirectional control channel data across the same GMSL2 link. GMSL2 data can be transported over Coaxial or Shielded-Twisted Pair (STP) cables. It operates at a fixed rate of 3 Gbps or 6 Gbps in the forward direction, and 187.5 Mbps in the reverse direction. The device is programmed through a local I2C/UART interface or across the link from a matching deserializer. The MAX96717 includes two I2C/UART pass-through channels, flexible GPIO, SPI tunnel, a built-in ADC, temperature sensor, and an extensive set of diagnostics for functional safety. Operation is specified over the automotive temperature range of -40°C to +105°C and the device is AEC-Q100 Grade 2 qualified. Data can be transmitted over low-cost 50 Ω Coax or 100 Ω STP cables that meet the GMSL2 channel specification.

Conclusion

As robotics moves into increasingly demanding environments and across diverse use cases, vision systems must evolve to support higher sensor counts, greater bandwidth, and deterministic performance. While legacy connectivity solutions will remain important for development and certain deployment scenarios, they introduce trade-offs in latency, synchronization, and system integration that limit scalability. GMSL, with its combination of high data rates, long cable reach, integrated power delivery, and bidirectional deterministic low latency, provides a proven foundation for building scalable robotic vision systems. By adopting ADI's GMSL serializer solutions, designers can accelerate the transition from prototype to production, delivering smarter, more reliable robots ready to meet the challenges of a wide range of real-world applications.

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