inemo™ platform - smac to... · inemo™ platform 10/12/2012 . ... inemo™ ahrs and sensor...

iNEMO™ Platform

Outline

• General concept and purpose

• Inertial position estimation and Sensor fusion

• Attitude and Heading Reference System (AHRS) / Kalman filtering

• Application example: Inertial Body Motion Reconstruction

• iNEMO™ Hardware

• STM32 microcontroller and peripherals

• Sensors (MEMS)

• External peripherals USB, UART, uSD, …

• iNEMO™ Software and Firmware

• Drivers

• FreeRTOS

• Tasks

• Host applications.

2

10/12/2012 iNEMO™ Platform

iNEMO™ Platform concept

• iNErtial MOdule produced by STMicrolectronics

• Combines accelerometers, gyroscopes and magnetometers to make

an integrated Inertial Measurment Unit (IMU)

• The IMU measures and reports velocity, orientation and gravitational

forces, using a combination of sensors.

3


ST MEMS: the way for the orientation 4

10/12/2012

The accelerometers sense linear acceleration

In static conditions, the projection of gravity on the

three axes allows tilt angles to be computed

The magnetometer senses the magnetic field

In static conditions, the projection of the

geomagnetic field on the three axes allows the

heading angle to be computed

The gyroscope measures the angular rate applied

to the device

In dynamic conditions, by integration of the 3-axis

angular rate, the 3D orientations can be computed

Sensor fusion and

AHRS algorithm

for 3D space orientation

iNEMO™ Platform

Inertial Measurement Unit (IMU)

• Electronic device that measures and reports on an object's velocity,

orientation, and gravitational forces

• Advantages

• Instantaneous output of position and velocity

• Completely self contained

• All weather global operation

• Error characteristics are known and can be modeled quite well

• Works well in hybrid systems (e.g., together with GPS)

• Disadvantages

• Position/velocity information degrade with time

• Expensive systems (usually).

5


Inertial navigation 1/3

• If we can measure the acceleration of an object we can

• Integrate the acceleration to get velocity

• Integrate the velocity to get position (dead reckoning)

• Then, assuming that we know the initial position and velocity we can

determine the position of the system at any time t

𝑥 𝑡 = 𝑎𝑥𝑑𝑡𝑑𝑡 = 𝑥 0 + 𝑣 0 𝑡 +𝑡

0

1

2𝑎𝑥𝑡

2𝑡

0

.

6



• The main problem is that the accelerometer can not tell the difference

between object acceleration and gravity: therefore we need to find a

way to separate the effect of gravity and of acceleration

• Two possible strategies are available:

• Keep the accelerometers horizontal so that they do not sense the gravity vector

(stable platform mechanization)

• Somehow determine in real time the angle between the accelerometer inclination

axis with respect to the horizontal, and then subtract the gravity components from

the measured acceleration (strapdown mechanization)

• The first strategy requires complex mechanical devices; the second is

based on an analytical or computational implementation.

7



• Strapdown navigation is based on the knowledge of acceleration and

orientation in an absolute angular reference

• Orientation is given by an "Attitude and Heading Reference System"

(AHRS)

• Then, the gravity acceleration components along the axes can be

computed and removed, and velocity and position are estimated.

8


AHRS and Sensor fusion 1/2

• Each AHRS sensor used has distinctive features and limitations

• Gyroscopes measure orientation by integrating angular velocities and the

accelerometer and magnetometer provide a noisy and disturbed but drift-free

measurement of orientation

• The combination of information from multiple sources and a suitable

system physical model provides a more reliable estimation of

orientation

• The Kalman filter is one of the most used sensor fusion algorithms,

whose discrete-time version can be easily implemented in software.

9


AHRS and Sensor fusion 2/2

• The Kalman filter suitably weights

the information sources with

knowledge on the signal

characteristics based on their

models, to make the best use of

all sensor data.

10


iNEMO™ AHRS and Sensor fusion

• The iNEMO System-on-Board includes different sensors and a sensor

fusion engine (based on an Extended Kalman Filter) running on the

microprocessor.

11


iNEMO™ Platform concept 12

10/12/2012

The iNEMO™ is a smart combination of

multiple MEMS sensors in a unique Inertial

Measurement Unit (IMU) targeting virtual

reality, platform stabilization, human

machine interfaces, and robotics.

iNEMO™ Platform

iNEMO™ features

• Absolute point tracking and motion tracking accuracy

• Immunity to magnetic interference for high

performance in real-world conditions

• Few user-calibration interruptions enabling innovative

and longer game play

• Reliable compass heading for accurate navigation

• Accurate direction enabling true augmented reality

applications.

13


14

• 1. Chest

• 2. Hips

• 3. Right arm

• 4. Right forearm

• 5. Left arm

• 6. Left forearm

• 7. Right femur

• 8. Right tibia

• 9. Left femur

• 10. Left tibia

1

2

3

4

5

7

8

9

10

The avatar on the screen follows the movements of the operator

6

Application example:

iBMR Body Motion Reconstruction 1/2

iNEMO™ Platform 10/12/2012

▪ Demo functions:

▪ A set of INEMO™

boards is used to

detect the body

movements

▪ All signals are

collected and sent to a

system showing an

avatar following the

human movement.

15

1

2

3

4

5

7

8

9

10

6

Application example:

iBMR Body Motion Reconstruction 2/2

iNEMO™ Platform 10/12/2012

iBMR_Video.wmv.mp4

iNEMO™ V2 Board1/2

• Main hardware components:

• STM32F103RE – Microcontroller

• LPR430AL – 2-axis gyro (roll, pitch)

• LY330ALH – yaw-axis gyro

• LSM303DLH – 6-axis geomagnetic module

• LPS001DL – pressure sensor

• STLM75 – temperature sensor

• LDS3985Mxxx – voltage regulator

• Extended connector

for wireless connectivity

• MicroSD™ card slot

• COM connector with RTS and CTS signals

• USB 2.0 full speed connection

• Reset button

• User LED and button

• Power supply switch (USB/VEXT).

16


iNEMO™ V2 Board 2/2 17


STM32 Microcontroller 1/2 18

10/12/2012

• Core: ARM 32-bit

CORTEX™-M3 CPU

• 72 MHz maximum frequency

1.25 DMPIS/MHz (Dhrystone 2.1)

• Single-cycle multiplication and

hardware division

• AMBA AHB/APB bus

• Memory:

• 512KB Flash, 64 KB RAM

• Flexible static memory controller

with 4 Chip Select. Supports

Compact Flash, SRAM, PSRAM,

NOR and NAND memories

• Clock, reset and power supply

management

• Low power: sleep, stop,

standby

iNEMO™ Platform

STM32 Microcontroller 2/2 • 3x 12-bit, 1ms A/D converters

• 2x 12-bit D/A converters

• DMA: 12-channel DMA controller

• Supported peripherals: timers, ADCs, DAC, SDIO, I2Ss, SPIs, I2Cs and UARTs

• Debug mode

• Serial wire debug (SWD) & JTAG interfaces

• Cortex-M3 Embedded Trace Macrocell™

• Up to 112 fast I/O ports

• 51/80/112 I/Os, all mappable on 16 external interrupt vectors

• Up to 11 timers

• Up to 13 communication interfaces

• 2x I2Cs, 5x UARTs, 3 SPIs, CAN, USB 2.0, SDIO

• CRC calculation, 96-bit unique ID.

19


iNEMO™ V2 on-board sensors

• Electronic and Micro Electro-Mechanical System (MEMS) technologies

• An integrated sensor usually includes

• The measuring instrument

• A transducer

• Signal conditioning circuitry

• An interface, which can be analog or digital.

20


Accelerometer/magnetometer 1/2

• The MEMS accelerometer is usually based on a miniaturized

mass-spring system, immersed in vacuum

• A capacitive or piezoresistive transducer reads out the electrical signal.

21


© OpenLearn LabSpace, Creative Commons Attribution-NonCommercial-ShareAlike 2.0 Licence

© University of British Columbia

Accelerometer/magnetometer 2/2

• LSM303DLH: 3-axis accelerometer and 3-axis magnetometer

• Linear acceleration full-scale of ±2 g / ±4 g / ±8 g and a magnetic field full-scale of

±1.3 / ±1.9 / ±2.5 / ±4.0 / ±4.7 / ±5,6 / ±8.1 gauss, both fully selectable by the user

• 2-wire I2C serial bus interface

• Can be configured to generate an interrupt signal by inertial

wakeup/free-fall events, as well as by the position of the device itself.

22


MEMS Gyroscope 1/2

• Usually implemented as a vibrating structure gyroscope

• A vibrating object tends to continue vibrating in the same plane as its support rotates

• As the plane of oscillation is rotated, the response detected by the transducer results

from the Coriolis term in its equations of motion (“Coriolis force”)

• Same principle as in the halteres of some kind of flying insects.

23


© San José State Universtiy

MEMS Gyroscope 2/2

• LPR430AL (2-axis) and LY330ALH (single-axis) are high

performance, low-power micro-machined gyroscopes capable of

measuring angular rate along pitch and roll axes

• Full scale of ±300 dps and capable of detecting rates with a -3 dB bandwidth up to

140 Hz

• The measured angular rate to the external world through an analog

output voltage.

24


Temperature sensor

• STLM75: Digital temperature sensor and thermal watchdog

• Temperature range: –55°C to +125°C

• Accuracy: ±2°C from –25°C to +100°C

• Low operating current: 125 μA

• Conversion time:150 ms

• 2-wire I2C/SMBus-compatible serial interface

• Output pin (open drain) can be configured for interrupt or

comparator/thermostat mode.

25


Pressure sensor

• LPS001D: piezoresistive pressure sensor (barometer)

• Pressure range: 300 -1100 mbar

• Resolution: 0.1 mbar

• Very low power consumption

• Embedded offset and span temperature compensation

• Embedded 16-bit ADC

• SPI and I2C interfaces.

26


iNEMO™ Firmware

• Open-source software project available for download http://www.st.com/internet/evalboard/product/250367.jsp

• STM32 libraries

(C and ARM Assembly)

• System configuration drivers (timer interrupt, DMA, power regulator, flash memory, ADC, …)

• Peripheral drivers I2C, UART, USB, SPI

• Timer programming

• GPIO interaction

• Sensor drivers

(mostly C)

• Accelerometer, gyroscope, magnetometer, pressure sensor, thermometer

• Operating System: FreeRTOS porting for STM32

(C and ARM Assembly)

• Sensor read-out and USB PC interaction library

(C/C++)

• ST proprietary AHRS libraries (closed-source).

27


http://www.st.com/internet/evalboard/product/250367.jsp

Accelerometer

driver • Set parameter

• Read data

• …

Microcontroller/sensor interaction

• Example: Accelerometer reading

28


CPU I2C LSM303DLH System bus

SDA

I2C driver

SCL

Operating System (OS)

• An OS is a set of software that manages computer hardware

resources

• Provides common services for computer programs (memory allocation, time

measurement, inter-task communication)

• Schedules tasks for efficient use of the system (time-sharing)

• Real-Time Operating System (RTOS)

• Embedded systems are designed for specific control functions with real-time

constraints

• An RTOS is an OS intended to serve real-time application requests

• Main goal is not high troughput, but guaranteeing quick and predictable response to

events

• Soft RTOS: can generally meet deadlines (occasional misses are not catastrophic)

• Hard RTOS: time-critical deadlines must be met (occasional misses cause catastrophic

system failures).

29


FreeRTOS

• Free and open source RTOS written in C/Assembly for small

embedded systems

• Simple and portable through 31 different architectures

• Split the workload in tasks

• Implements a Round Robin priority-based task scheduler with

different algorithms

• preemptive

• cooperative

• hybrid

• Provides inter-task communication mechanisms.

30


FreeRTOS: scheduling and task switching

• Event-driven (e.g. timeout, synchonization events)

• Switch among different states

• Idle task always running

• Timing based on a tick rate.

31


iNEMO™ Firmware behavior 32

10/12/2012

Boot phase:

microprocessor and

peripheral initialization

FreeRTOS startup

Fre

eR

TO

S

iNemoCmd

task

iNemoData

task

iNEMO™ Platform

USB

IRQ

TIM2

IRQ

Receives requests from USB and

sends suitable answers

When active, periodically reads

sensor data and sends them via the

USB connection.

[…]

iNEMO™ suite software and libraries

• Available for download at http://www.st.com/internet/evalboard/product/250367.jsp

• Frame definition for USB communication

• Example:

• C/C++ iNEMO™ interaction library for the development of user

applications

• Graphical interface for sensor interaction (iNEMO™ Suite).

33




iNEMO™ and the SMAC Project

• Smart systems such as the iNEMO platform are currently being

studied within the FP7 SMAC Project, whose main goals are:

• The development of a co-simulation and co-design environment which is aware

(and thus considers) the essential features of the basic subsystems and

components to be integrated;

• The development of modeling and design techniques, methods and tools that,

when added to the platform, will enable multi-domain simulation and optimization at

various levels of abstraction and across different technological domains

• The SMAC platform will allow to successfully address the following

grand challenges related to the design and manufacturing of

miniaturized smart systems:

• Development of innovative smart subsystems and components demonstrating

advanced performance, ultra low power and the capability of operating under

special conditions (e.g., high reliability, long lifetime)

• Design of miniaturized and integrated smart systems with advanced functionality

and performance, including nanoscale sensing systems, possibly operating

autonomously and in a networked fashion.

34


References

• iNEMO™ V2 (STEVAL-MKI062V2):


• iNEMO™ M1:

http://www.st.com/internet/analog/product/253162.jsp

• FreeRTOS: http://www.freertos.org/

• N. Abbate, A. Basile, C. Brigante, A. Faulisi, “Development of a MEMS based

wearable motion capture system”, IEEE Conference on Human System

Interaction (HSI), 2009, pp. 255-259

• N. Abbate, I. Aleo, A. Basile, C. Brigante, A. Faulisi, “Design of an Inertial Motion

Module”, IEEE International Conference on Robotics and Automation (ICRA),

2011, pp. 1-4

• C. Brigante, N. Abbate, A. Basile, A. Faulisi, S. Sessa, “Towards Miniaturization

of a MEMS-Based Wearable Motion Capture System”, IEEE Trans. on Industrial

Electronics, Vol. 58, N. 8, Aug. 2011, pp. 3234-3241

35






http://www.freertos.org/

inemo™ platform - smac to... · inemo™ platform 10/12/2012 . ... inemo™ ahrs and sensor...

Documents