LSM6DS3TR-C
6-Axis MEMS IMU with MLC · Machine Learning Core · ±2000dps / ±16g · LGA-14L · STMicroelectronics
| Part Number | LSM6DS3TR-C |
|---|---|
| Manufacturer | STMicroelectronics |
| Sensor Type | 6-Axis (3-Axis Gyro + 3-Axis Accel) |
| Gyroscope Range | ±125 / ±250 / ±500 / ±1000 / ±2000 dps (selectable) |
| Accelerometer Range | ±2 / ±4 / ±8 / ±16 g (selectable) |
| MLC (Machine Learning Core) | Built-in — on-chip ML classification |
| FSM (Finite State Machine) | Built-in — decision tree processing |
| Current Consumption | 0.55 mA typical (combo normal mode) |
| FIFO Buffer | 9 KB — largest in class |
| Package | LGA-14L (2.5×3.0×0.83mm) |
| Supply Voltage | 1.71 V – 3.6 V |
| Operating Temperature | −40°C to +85°C |
| MLC Features | On-chip machine learning classification using embedded decision trees |
|---|---|
| FSM Features | Finite State Machine for gesture and motion pattern recognition |
| MLC Input Features | Up to 16 features from gyro, accel, and external sensors |
| Decision Trees | Up to 8 decision trees with 64 nodes each |
| Wake-up from MLC | Interrupt-driven wake from low-power mode on pattern match |
| Use Cases | Vibration pattern detection, flight mode recognition, predictive maintenance |
| Digital Interface | I²C up to 400 kHz, SPI up to 10 MHz |
|---|---|
| I²C Address | Selectable (0x6A or 0x6B via SA0 pin) |
| SPI Mode | Mode 0 or Mode 3 supported |
| FIFO Features | 9 KB, batch mode, pattern detection, watermark |
| Interrupt Pin | INT1 and INT2, configurable for MLC/FSM events |
| Self-Test | Built-in self-test for both gyro and accel |
| Register Compatibility | Compatible with LSM6DSO register map |
| Pins | 14-pin LGA (SDI, SDO, SCLK, CS, SA0, INT1, INT2, VDDIO, GND, VDD, OCS, NC) |
| Part Number | LSM6DS3TR-C |
|---|---|
| Orderable Qty | 1 pcs – 10,000+ pcs |
| Price (1–9 pcs) | Contact for quote |
| Price (10–99 pcs) | Contact for quote |
| Price (100–499 pcs) | Contact for quote |
| Price (500+ pcs) | Best pricing available |
| Lead Time (stock) | 3–7 business days |
| Packaging | Tape & Reel (T&R) |
| RoHS Compliant | Yes (Pb-free) |
Please confirm exact parameters with manufacturer datasheet.
The LSM6DS3TR-C is a unique 6-axis MEMS inertial measurement unit from STMicroelectronics that distinguishes itself from conventional IMU sensors through its built-in Machine Learning Core (MLC) and Finite State Machine (FSM). While most IMU sensors merely output raw or filtered sensor data to the host MCU, the LSM6DS3TR-C can perform on-chip ML classification and decision processing — recognizing vibration patterns, flight modes, and motion gestures without waking the main flight controller. This makes it exceptionally well-suited for intelligent drone applications where power efficiency and real-time edge AI processing are critical.
The Machine Learning Core (MLC) in LSM6DS3TR-C implements embedded decision trees that can classify sensor data in real-time. For UAV applications, this enables sophisticated features such as automatic flight mode recognition (detecting hover, forward cruise, aggressive maneuvering), vibration pattern analysis for propeller balance monitoring, and predictive maintenance alerts based on motor vibration signatures. Since the MLC processing happens on the sensor itself, the main flight controller MCU (STM32H743, STM32F765, etc.) can remain in low-power mode until a significant event is detected, dramatically reducing overall system power consumption.
Complementing the MLC is the Finite State Machine (FSM), which enables complex motion pattern recognition through state-based decision processing. The FSM can be configured to detect specific flight events — such as free-fall detection, crash impact detection, or specific acrobatic maneuver patterns — and generate interrupts to wake the host MCU only when needed. This architecture is particularly valuable for long-endurance survey drones and delivery UAVs where maximizing flight time is essential. The 9 KB FIFO buffer (the largest in its class) allows extended batch sensor reads, further reducing bus traffic and MCU wake-up frequency.
The sensor supports both SPI (up to 10 MHz) and I²C (up to 400 kHz) interfaces, with a selectable I²C address (0x6A or 0x6B) for multi-sensor bus configurations. With a typical current consumption of 0.55 mA in combo normal mode and an industrial operating temperature range of −40°C to +85°C, the LSM6DS3TR-C delivers reliable performance in demanding UAV environments. The LGA-14L package (2.5×3.0×0.83mm) is pin-compatible with other ST LSM6DS series sensors, simplifying design upgrades and multi-sourcing strategies.
Key Features
- Unique MLC (Machine Learning Core) — on-chip ML classification without waking main MCU
- FSM (Finite State Machine) — embedded decision processing for motion pattern recognition
- 9 KB FIFO buffer — largest in class, enables extended batch reads and reduced bus traffic
- Intelligent power management — MCU can sleep while MLC/FSM monitor flight patterns
- Wide gyro range: ±125 to ±2000 dps — configurable for different UAV types
- Both SPI (10 MHz) and I²C (400 kHz) interfaces with selectable addresses
- Compact LGA-14L package (2.5×3.0×0.83 mm) — pin-compatible with LSM6DS series
- Ideal for smart drones: flight mode recognition, vibration monitoring, predictive maintenance
Need LSM6DS3TR-C for Your Smart Drone Project?
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The LSM6DS3TR-C features ST's proprietary Machine Learning Core (MLC) and Finite State Machine (FSM). Please confirm exact ordering code and package specifications before production purchase. For MLC feature integration, ST provides the Unico GUI configuration tool and MLC software examples. The LGA-14L package is pin-compatible with LSM6DSO and LSM6DSLTR, simplifying design upgrades. Contact UAVCHIP for datasheet, MLC configuration guide, and volume pricing for intelligent UAV production.
How on-chip ML classification in LSM6DS3TR-C enables intelligent UAV applications. Flight mode recognition and vibration monitoring use cases.
Read Article →Using IMU sensor MLC to detect propeller imbalance and motor wear. Predictive maintenance for commercial drone fleets.
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