Precise navigation of drones and autonomous robots It no longer relies solely on GPS: when the signal fails, inertial sensors come into play, and that's where high-end FOG IMUs and MEMS IMUs shine. On aerial or ground platforms moving in complex environments, choosing the right sensor makes the difference between stable guidance and an out-of-control vehicle.
In the following lines we will go into detail about the IMU FOG, MEMS and INS Focused on drones and robotics: what they are, how they work, how they differ, their precision, weight, cost, and real-world applications. The goal is for you to develop a clear understanding of the best technology for your project, whether it's a small UAV, a ground robot, an electro-optical capsule, or a critical defense system.
IMU, INS and inertial sensors: basic concepts
An IMU (Inertial Measurement Unit) It is, essentially, a sensor module that measures how a body moves and orients itself in three-dimensional space. To do this, it integrates at least three gyroscopes and three accelerometers mounted orthogonally (X, Y, Z axes) and, in many cases, also includes three magnetometers to measure the magnetic field.
The IMU's gyroscopes are responsible for measuring the angular velocity (how fast the drone or robot rotates around each axis), while the accelerometers record the specific strengthThat is, the acceleration experienced by the system minus gravity. When we add magnetometers, we also obtain information on three-dimensional magnetic direction, useful as an additional reference.
One step further is the INS (Inertial Navigation System)An INS includes an IMU as the heart of the system, but also powerful electronic processing, advanced statistical filtering (such as Kalman filtering) and, usually, a GNSS receiver (GPS, GLONASS, Galileo, BeiDou, etc.) to provide absolute position references when available.
The INS takes the raw outputs from the IMU (accelerations and angular velocities), integrates them over time, and, referencing them to a known starting point, calculates in real time the attitude, position, linear velocity, and motion vector of the vehicle. In air navigation it is also known as AHRS (Attitude and Heading Reference System).
The great advantage of INS is that they allow you to continue browsing even when there is no signal. GNSS signalIn a tunnel, under dense vegetation, in a confined urban environment, or underwater in the case of a submarine, the system uses dead reckoning: it starts from a reliable initial position and accumulates changes in orientation and displacement. The drawback is that any small inaccuracy eventually leads to increasing errors over time.
Why drones and robots need good IMUs
In a drone, the IMU is part of the autopilot or flight controller It is responsible for ensuring the aircraft maintains stability, follows smooth trajectories, and responds correctly to flight commands. Without a quality IMU, any gust of wind, engine vibration, or minor disturbance would result in oscillations and loss of control.
The IMU of a UAV continuously measures the orientation, accelerations, and angular ratesThis data is then combined using a Kalman filter along with information from other sensors (GNSS, barometer, magnetometer, etc.). From this fusion, navigation variables such as attitude, linear speed, and estimated position are generated, even when there is no satellite coverage.
Something similar happens in terrestrial robotics: the mobile robots They use the IMUs to maintain the balance, following precise trajectories and estimate its own movement, especially when external references (beacons, machine vision, GNSS) become unreliable or temporarily disappear.
Therefore, in demanding applications, IMUs with high stability, good vibration resistance and excellent thermal performanceA robust and precise IMU dramatically improves attitude control, enabling smoother flight and much more reliable navigation in complex situations.
In advanced autopilot systems, such as those used in professional UAVs, it is common to find configurations of redundant IMUsFor example, modules with three internal IMUs and a barometer, or even architectures with up to nine IMUs for environments where safety is critical. Some of these IMUs are mounted with mechanical vibration isolationwhile others are rigidly attached to the chassis to extract very specific information, such as estimating rotor RPM in helicopters.
IMU technologies: Standard MEMS, High-precision MEMS, and FOG
When talking about FOG IMU sensors for drones and robotsIt is important to clearly compare the main technologies used today: standard MEMS IMU, high-precision MEMS IMU and fiber optic gyroscope-based (FOG) IMUs, without forgetting variants with ring laser gyroscopes (RLG) and other niche technologies.
IMU MEMS standard These are the ones we find in consumer electronics: mobile phones, video game consoles, small recreational drones, and simple robots. They offer moderate precision, sufficient for many tasks, at a very low cost and in a minimal size.
When we make the leap to the High-precision MEMS IMUWe enter the league of industrial-grade and light military systems. These units can reach bias instabilities on the order of 0,1°/h, approaching what some basic FOG IMUs offer, but with a generally lower cost and volume.
IMU FOG (Fiber Optic Gyro)These, meanwhile, belong to the high-end range of inertial sensors. They achieve polarization instabilities as low as 0,001°/hThis makes them ideal for long-duration missions and for systems where dead reckoning must remain accurate for many hours without external assistance.
In summary, we can say that standard MEMS IMUs cover a wide range of consumer and industrial applications, high-precision MEMS come very close to FOG performance in some specific cases, and FOG remain the benchmark when we talk about extreme stability and minimal drift.
IMU MEMS: advantages, limitations and applications
Technology MEMS (Micro-Electro-Mechanical Systems) It allows the fabrication of tiny inertial sensors on silicon wafers, sharing processes with the semiconductor industry. This has dramatically increased the availability of very compact, lightweight, and inexpensive gyroscopes and accelerometers, perfect for integration into almost any device.
In a typical MEMS IMU, the quartz or silicon gyroscopes They function as Coriolis sensors: a vibrating structure reacts to rotation, and this response is translated into an electrical signal that is processed by the integrated electronics. Accelerometers, on the other hand, are based on a test mass suspended by micro-springs, whose deformation is proportional to the acceleration experienced.
MEMS IMUs are notable for their Small size, weight and power (SWaP)This makes them ideal for small UAVs, compact robots, wearables, and thousands of embedded systems. Their cost is significantly lower than that of FOG or RLG IMUs, allowing for basic inertial navigation to be implemented in a wide variety of platforms.
In advanced designs, MEMS have greatly improved their environmental robustnessThey withstand shocks, strong vibrations, and temperature changes well, which is crucial for drones subjected to unbalanced propellers, aggressive maneuvers, or hard landings. Therefore, many high-end IMUs for UAVs combine carefully selected MEMS with sophisticated calibration and filtering techniques.
At the upper end of the spectrum are the High-precision MEMS IMUThese significantly reduce noise, drift, and bias, achieving polarization instability as low as 0,1°/h. While they don't reach the levels of a top-tier FOG, they offer a very attractive balance of precision, cost, and size for many industrial drones and advanced robots.
IMU FOG: Maximum stability for critical missions
IMUs based on fiber optic gyroscopes (FOG) They use the Sagnac effect to measure rotation: two beams of light are injected into the same coiled optical fiber, circulating in opposite directions, and as the system rotates, a phase difference is generated that can be detected by interferometry.
This optical technology allows reaching levels of stability and low drift which MEMS still cannot match in the higher range. With polarization instabilities on the order of 0,001°/h, FOG IMUs are especially well-suited for extended dead reckoning, where the accumulated error must be kept extremely low for hours or days.
Some modern FOG IMUs combine three-axis FOG gyroscopes with precision MEMS accelerometersThis achieves the best of both worlds: extremely high-quality gyroscopic motion and very compact and robust accelerometers. These types of solutions are used in high-end autonomous vehicles, electro-optically stabilized capsules, submersibles, missiles, and platforms where failure is not an option.
In the field of drones and robots, FOG IMUs are reserved for mission critical applications: Large UAVs dedicated to long-range inspection, defense platforms, unmanned vehicles for naval or land environments that must maintain accuracy even with GNSS denied for long periods.
Obviously, these features come at a cost: a FOG IMU is larger, heavier, and considerably more expensive than a MEMS IMU. However, in systems where absolute precision and reliability are paramount, the investment is more than justified.
Other gyroscope technologies: RLG and mechanical gyroscopes
Although in the context of drones and robots the main battle is fought between MEMS and FOGIt is worth knowing about other gyroscope technologies that are still very present in high-level applications, especially in the aerospace and naval sectors.
The ring laser gyroscopes (RLG) They are also based on the Sagnac effect. A single laser, usually a helium-neon mixture, is split into two beams that circulate in opposite directions within a ring-shaped cavity. As the assembly rotates, the interference pattern between the two beams changes, and the angular velocity is derived from this.
Furthermore, the classic mechanical gyroscopes They remain unbeatable in very long-term stability in certain cases. They consist of a heavy rotor mounted on gimbals that maintains its orientation due to the conservation of angular momentum. Although they are bulky and heavy, on platforms where this is not critical (such as large submarines or some aircraft) they continue to be used as the primary reference.
In practice, RLG, FOG, and MEMS gyrocompasses cover almost the entire range of performance characteristics. Whereas the mechanical turns They are being partially replaced, but they still have their niche where maximum stability is sought and space is not a limiting factor, something unusual in drones but common in large ships and submarines.
Accelerometers and magnetometers in inertial systems
The accelerometers The sensors that are part of an IMU measure changes in velocity over time. Conceptually, they are a mass suspended by a spring on a sensing axis: when the system accelerates, the mass moves, the spring is compressed or stretched, and the electronics translate that displacement into a measurement of acceleration, usually in m/s².
There are multiple technologies for implementing them, but in drones and robots, the following predominate: MEMS accelerometerswhich allow several axes to be packaged on the same chip, with sufficient sensitivity to measure everything from intense vibrations to smooth flight maneuvers or movement.
The magnetometersThese components, in turn, are responsible for measuring the local magnetic field. An analog compass is the most basic example, but modern systems use technologies such as the Hall effect, magnetodiodes, MEMS Lorentz force sensors, fluxgates, and other variations.
In many IMU/INS systems for drones and robots, MEMS magnetometers provide a three-dimensional bearing reference This is very useful for supplementing rotation and acceleration data, especially at low speeds and in the absence of other references. However, care must be taken to avoid magnetic interference from motors, high-current cables, or nearby metal structures.
By combining gyroscopes, accelerometers, and magnetometers on three axes each, we obtain what is called an IMU of 9 axescapable of providing a very complete picture of the vehicle's attitude and environment, provided that the sensor fusion algorithms are well designed.
Kalman filtering and sensor fusion
El Kalman filter It is one of the fundamental pillars of any modern INS. It is a recursive estimation algorithm that combines measurements from different sensors with a mathematical model of the system to obtain the best possible estimate of the state (position, velocity, attitude), weighting each source according to its uncertainty.
In the first phase, the filter uses the dynamic model from the drone or robot to predict how its state should evolve in the next instant. In the second phase, it compares that prediction with the actual measurements from the IMU, GNSS, and other sensors, and adjusts the estimate by applying a weighted average based on the expected accuracy of each data point.
This process is repeated in real time, typically at frequencies on the order of 100Hz to 1kHz in demanding systems, which allows for very smooth and stable navigation data even when one of the information sources is temporarily degraded or introduces noise.
Thanks to Kalman filtering, IMUs can work side-by-side with GNSS receivers, barometers, wheel odometry, artificial vision or LIDAR, achieving a robust and precise navigation that takes advantage of the strengths of each sensor and minimizes its weaknesses.
Without this type of fusion, neither MEMS IMUs nor FOGs, however good they may be, could offer on their own the level of precision and stability required by many current applications in drones, robotics, automotive or defense.
IMU and INS applications in drones, robots, and other vehicles
The applications of IMU and INS systems They extend to virtually any vehicle that moves in three-dimensional space. In the environment of drones and robots, some of the most common are the following.
En road vehicles (cars, trucks, buses, motorcycles), IMUs and INS are integrated into Advanced Driver Assistance Systems (ADAS) and autonomous driving platforms to estimate vehicle dynamics, stabilize control systems and maintain navigation when GNSS is degraded, for example in tunnels or between tall buildings.
En manned and unmanned aircraftIn both commercial and military applications, INS are a key component for guiding the trajectory, stabilizing the attitude, assisting in landing and takeoff in adverse conditions, and generally ensuring that the pilot (human or automatic) has reliable information at all times.
In the field SUVMilitary, agricultural, and construction vehicles use IMU and INS to navigate terrain without clear landmarks, verify machinery orientation, record test data, and coordinate precise movements in complex operations.
La Space and naval navigation This is perhaps the most extreme example: satellites, spacecraft, ships, and submarines rely on highly accurate INS to determine their attitude and position when external references are scarce or nonexistent. In submarines, for example, INS is practically the only reliable means of knowing exactly where they are when navigating submerged for extended periods.
In the field of robotics and guided weapons systemsFrom missiles to land and sea platforms, high-performance FOG and MEMS IMUs enable highly accurate trajectories, autonomous guidance, and stabilization of sensitive payloads, such as turrets or electro-optical sensors.
How to choose the best IMU for your drone or robot
Selecting the right IMU for a drone or robot isn't simply a matter of looking at a spec sheet and choosing the cheapest or most accurate option. Several factors need to be balanced. key factors so that the global system makes technical and economic sense.
The first criterion is usually the sensor accuracy and stabilityThis is where parameters such as noise, drift, bias instability, and linearity specifications come into play. In drones or robots that must operate with GNSS denied for extended periods, it is especially important that the bias be low so that estimation errors do not skyrocket.
La calibration Also critical is a well-calibrated IMU, with factory-installed systematic error compensation (and, if possible, field recalibration), which significantly reduces error accumulation in dynamic environments. In high-quality products, this calibration is performed at different temperatures and conditions to ensure stable performance.
Another important point is the dynamic range and resolutionFor an acrobatic drone or a missile, the system must withstand high accelerations and angular velocities without saturating, while for a precision robot, fine resolution in small movements might be more important. Adjusting the sensor range to the application prevents data loss or the introduction of unnecessary noise.
On battery-powered platforms, such as UAVs and UGVs, the energy consumption It weighs a lot. A low-power IMU extends battery life and reduces heat generation, which can allow for more compact or less ventilated cases. MEMS IMUs usually outperform FOG IMUs in this regard.
La mechanical and environmental robustness It shouldn't be underestimated: intense vibrations, shocks, thermal shock, or humidity can quickly ruin a poorly designed IMU. For harsh applications (defense, aerospace, mining, etc.), sealed enclosures, IP67-rated protection, compliance with standards like MIL-STD-810G, and vibration-resistant internal designs are essential.
El form factor (size and weight) It directly influences integration: a small and lightweight IMU fits better in compact drones and robots, while in large systems a bulkier unit can be accepted if it provides superior accuracy.
Finally, we must not forget the integration and compatibilityCommunication interfaces (USB, Ethernet, CAN, serial), refresh rate (outputs at 100 Hz, 500 Hz or even 1 kHz), support for standard protocols and ease of connection with the autopilot or DAQ system are key aspects to avoid complicating your life in development.
Examples of IMU/INS solutions and third-party compatibility
In the current market we can find everything from simple IMUs for robot prototyping to complete INS systems ready to be integrated into test vehicles, professional drones or ADAS test platforms.
There are compact GPS-assisted navigation systems that combine MEMS inertial sensors with multi-constellation GNSS receivers (GPS, GLONASS, BeiDou, Galileo, WAAS, EGNOS, GAGAN, etc.), with output speeds on the order of 100 Hz, USB connectivity and sealed housings with environmental resistance certifications, designed for vehicle dynamics measurements and basic navigation.
In the upper segment there are Ethernet-based INS platforms with Dual-frequency GNSS receivers with RTK capability With centimeter-level accuracy, dual antennas for precise static heading estimation, PPS outputs for external synchronization, and support for DGNSS or SBAS augmentation, these systems are geared towards autonomous vehicle testing, advanced dynamics measurements, and applications requiring maximum precision.
There are also pure inertial units, without an integrated GNSS receiver, that offer high sampling rates (up to 500 Hz or more) and they connect via USB or other interfaces, widely used for dynamic measurement, stabilization and attitude control when absolute positioning is resolved by other means.
Many data acquisition and analysis software programs are compatible with IMU and INS from third-party manufacturersThis facilitates the integration of equipment from brands such as VectorNav, iXblue, Inertial Labs, and other specialized providers. For example, this allows an autopilot to interact with a high-end external FOG IMU when the required accuracy exceeds that of the internal sensors.
Likewise, some advanced inertial units, such as certain UF600 models, combine a three-axis fiber optic gyroscope and MEMS accelerometers to offer a compact, lightweight and high-precision solution, very suitable for attitude control and inertial navigation in autonomous driving, UAVs, electro-optical capsules, submersibles and complex guidance systems.
Given all of the above, it is easy to understand why the IMU MEMS and FOG They have become the cornerstones of modern navigation in drones and robots: the former democratize access to inertial navigation with very small sizes and costs, while the latter cover the most delicate missions thanks to their extreme stability; choosing the best combination for each project, relying on well-designed INS and good sensor fusion, is the key for these autonomous platforms to move accurately even when GNSS disappears from the map.
