Q&A: Advancing Autonomous Robotics with Silicon Photonics Optical Gyroscope Technology

Ensuring accurate positioning and orientation in challenging environments is paramount to the ability of autonomous robotics to perform tasks seamlessly, safely and efficiently. Traditional GPS-based solutions often fall short in areas where signal availability is limited or absent, and this represents a major issue for any autonomous system relying on GPS.

To address this, Anello Photonics, based in Santa Clara, Calif., has developed an innovative solution that combines advanced optical gyroscope technology with an AI-based sensor fusion engine. The breakthrough sensor technology, known as Anello SiPhOG (Silicon Photonics Optical Gyroscope), is based on integrated photonic system-on-chip technology and offers precise positioning even in locations where conventional GPS systems fail. This approach further allows autonomous operations to be conducted independently and without interruption for extended periods of time.

In this Q&A with Dr. Mario Paniccia, CEO and co-founder of Anello Photonics, we explore the challenges of integrating Anello’s technology to a wide array of applications in industries, such as robotics, agriculture, drones, trucking, and construction, as well as defense and national security.

Anello’s SiPhOG—Silicon Photonics Optical Gyroscope—is an integrated photonic system-on-chip (SoC).

Machine Design: What are the main challenges with integrating autonomous robots with existing infrastructure or legacy systems?

Dr. Mario Paniccia: The primary hurdle is compatibility—many older systems were simply not designed to communicate with modern robotic platforms. This results in issues with data exchange, synchronization and maintaining efficiency in operations. These legacy systems often lack the advanced sensors, computational power and real-time data processing capabilities needed to seamlessly integrate with autonomous robots.

This mismatch can lead to not only poor performance but operational inefficiencies and sometimes even safety risks if the robots cannot adapt to the environment or to the existing infrastructure. To overcome these barriers, substantial investments in upgrades and retrofitting are required to make the infrastructure autonomous robotic-ready.

MD: Can you explain your advanced optical gyroscope technology and AI-based sensor fusion engine? What problem does it solve?

MP: An optical gyroscope or fiber optic gyro is a sensor that measures angular velocity using the interference of light. Today this technology is built using big bulky and expensive optical components that are hand assembled. At Anello we have taken a radically different approach to designing the optical gyroscope using integrated silicon photonics. With silicon photonics we can combine all the optical components (splitters, couplers, phase modulators, TM filters, detectors, etc.) into a single photonic integrated circuit (PIC).

This PIC is fabricated in a high-volume fabrication facility, just like other semiconductor chips. This allows us to produce a small, compact, low power yet high performance optical gyro which we call SiPhOG (Silicon Photonics Optical Gyro), that can be produced in high volume. When we combine the SiPhOG with a CPU, GPS and Anello’s AI-based sensor fusion engine, the result is a high-performance navigation system that can provide highly accurate positioning and orientation information in real-time, even in GPS-denied or degraded environments such as urban canyons, parking structures and tunnels.

In addition to enhancing accuracy and reliability in GPS-degraded environments, these SiPhOG-based systems are capable of operating in harsh environments, are insensitive to vibration and are significantly less sensitive to temperature than existing MEMS-based solutions.

MD: What types of sensors and data-processing would be required to ensure continuous, uninterrupted robotic operation?

MP: Continuous, uninterrupted operation of autonomous robots can be improved by using a combination of sensors and robust AI data-processing systems. Some of these elements could include:

Optical gyroscopes. Measure rotational movements with high accuracy, even in GPS-denied environments.
Accelerometers. Detect changes in linear velocity and ensure the robot can track its motion in three-dimensional space.
Magnetometers. Provide directional information by detecting magnetic fields, aiding in orientation.
Cameras and LiDAR. Help the robot “see” and understand its surroundings, which are essential for obstacle avoidance and path planning.

On the data processing side, the Anello AI-based sensor fusion engine is critical since it collects, analyzes and integrates data from multiple sensors to make real-time decisions about the robot’s movements. The AI engine continually adjusts the robot’s course based on the combination of the various sensors to ensure the robot maintains accurate positioning, even when the environment presents new obstacles or changes in the landscape.

MD: Does this solution present new risks or exposure? In other words, what are the data-collection limitations? Should we still be concerned about cybersecurity and data integrity?

MP: While the integration of inertial navigation systems based on Anello’s SiPhOG and Anello’s AI sensor fusion technology significantly improves robotic autonomy and precision, one must always be thinking about the quality of the data. The Anello technology has been tested in real jamming and spoofing environments.

Our AI algorithms constantly monitor the real-time position of the device and compare it to the GPS position every 10 milliseconds. When a deviation is detected between the two positions, our system analyzes the difference and switches to Anello to ensure precise navigation. Additionally, the Anello AI algorithms also significantly improve the tech’s resilience to jamming and spoofing.

At Anello, safety and security are top priorities. For instance, the Anello GNSS INS operates on an ASIL-D rated CPU using the PXROS RTOS, ensuring a high level of safety and security required for safety-critical applications. A hardware built in test (BIT) output line signals fault detection, alongside diagnostic messages and the BIT data word, ensuring data integrity for safety-critical applications.

MD: Who uses this technology? Can you describe applications in industrial robotics and aerospace & defense?

MP: Anello Photonics’ advanced technology serves a broad range of industries, including robotics, aerospace & defense, construction, agriculture and the autonomous vehicle industry. Our core technology, the Anello SiPhOG, is integrated into our inertial navigation systems, which enable high-precision navigation and positioning for autonomous systems across a wide spectrum of applications. Some of these applications are listed below.

Industrial robotics. Anello’s technology provides robotics systems with critical feedback on orientation and movement in real-time. This is especially beneficial in manufacturing and automation, where precise motion control is essential for efficiency and accuracy. The sensors enable robots to operate autonomously in complex, dynamic environments, improving productivity and operational reliability.
Aerospace. Anello’s X3 IMU is used in unmanned aerial vehicles (UAVs) to provide high precision inertial measurements to enable navigation in GPS-denied or GPS-challenged environments. Anello has an open-source driver to seamlessly read in the X3 IMU data into PX4 and Ardupilot.
Construction. Anello’s navigation systems are applied in autonomous construction machinery, helping with precision during planning and execution. In areas with limited GPS signals, these systems enhance accuracy in tasks like excavation, material handling and site surveying, improving overall efficiency and safety on construction sites.
Agriculture. In agriculture, the technology supports autonomous farming equipment by providing precise navigation and positioning, even in areas like orchards and under dense canopies where GPS signals are degraded. This helps optimize fieldwork by enhancing accuracy in planting, spraying and harvesting, which ultimately leads to increased yield and reduced waste.
Autonomous vehicles. Our sensors are also key to the development of autonomous vehicles, including cars and trucks. The technology ensures precise positioning, navigation and orientation for autonomous driving systems, allowing these vehicles to operate safely and efficiently in complex and dynamic environments such as urban canyons, tunnels and parking garages where GPS signals may be weak or entirely unavailable.
Maritime. Anello recently released its Maritime INS product, an innovative solution for Maritime applications such as Unmanned Surface Vessels (USV) and Unmanned Underwater Vessels (UUV). The Maritime INS uses three SiPhOGs and Anello’s AI sensor fusion engine to create a navigation solution in open sea, near-shore or under sea environments, enabling operation in GPS-denied or contested environments.
Defense. Autonomous systems such as Unmanned Ground Vehicles (UGVs), USVs, UUVs and UAVs are increasingly dominating the defense sector across land, air and sea applications. Each of these systems must be resilient to GPS jamming and spoofing, which requires highly accurate optical gyroscope-based INS solutions. Anello’s IMU+, X3, GNSS INS and Maritime INS are used in various defense use cases to enable stability and continuous navigation and guidance capabilities in GPS-denied environments and ensure mission success.

As autonomous systems are implemented in industries ranging from robotics and agriculture to defense and maritime navigation, the demand for precise, resilient and continuous navigation continues to grow exponentially. In order for these autonomous systems to maintain reliability they must be able to navigate environments where GPS signals are weak, obstructed or intentionally disrupted.

By leveraging advanced optical gyroscopes and AI-based sensor fusion engines, autonomous systems acquire positioning and orientation information in real time, allowing systems to operate independently, even in the most challenging conditions such as urban canyons, tunnels, dense orchards or jammed/spoofed environments.

The fusion of optical gyroscopes and AI for autonomous navigation represents a foundational shift in how autonomy can be achieved and broadens the potential use cases for today’s autonomous platforms. As autonomy continues to advance, these innovative optical gyroscope-based navigation solutions are making real-world applications possible—paving the way for a more connected, intelligent and self-directed autonomous future.