Signals, Instruments, and Systems W7. Embedded Systems General Concepts and

Transcription

1 Signals, Instruments, and Systems W7 Introduction to Hardware in Embedded Systems General Concepts and the e-puck Example

2 Outline General concepts: autonomy, perception, p action, computation, communication Examples of embedded systems The e-puck miniature robot General architecture t Perception (Sensors) Action (Actuators) Computation (Microcontroller) Communication (Transceivers)

3 General Concepts for Embedded Systems

4 What is an Embedded System? From Wikipedia: An embedded system is a special-purpose p p computer system designed to perform one or a few dedicated functions often with real-time computing constraints. It is usually embedded as part of a complete device including hardware and mechanical parts. In contrast, a general-purpose computer, such as a personal computer, can do many different tasks depending on programming.

5 What is Challenging in Designing Embedded Systems? Computation is subject to physical and resource constraints such as timing, deadlines, memory restrictions, and power consumption requirements. The traditional abstraction of separating software from the hardware is more difficult. Hardware and software are integrally intertwined. But: hardware components are becoming more and more flexible, cheap, small, and standardized. The design complexity is shifting to software! Your role as Environmental Engineers: get enough background to contribute to the software side with your domain knowledge and collaborate with electrical and computer engineers.

6 Autonomy Different levels/degrees of autonomy Energetic level Sensory, motor, and computational level Decisional level Needed degree of autonomy depends on task/environment in which the unit has to operate Environmental unpredictability is crucial: robot manipulator vs. mobile robot vs. sensor node

7 Autonomy The Impact of Controllable Mobility Task Complexity Human-Guided Robotics State of the Art in Mobile Robotics Distributed ib t Autonomous Robotics? Autonomous Robotics Autonomy Research Industry

8 Perception-to-Action Loop sensors actuators Per rception Computation Action Environment Note: real-time aspect emphasized!

9 Perception - Sensors Propioceptive ( body ) vs. exteroceptive ( environment ) Ex. proprioceptive: motor speed/robot arm joint angle, battery voltage Ex. exteroceptive: distance measurement, light intensity, sound amplitude Passive ( measure ambient energy ) vs. active ( emit energy in the environment and measure the environmental reaction ) Ex. passive: temperature probes, microphones, cameras Ex. active: laser rangfinder, IR proximity sensors, ultrasound sonars [Adapted from Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

10 4a 4a - Perception - Sensors 10 Classification of Typical Sensors [From Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

11 4a 4a - Perception - Sensors Classification of Typical Sensors 11 [From Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

12 4a 4a - Perception - Sensors 12 General Sensor Performance Range Upper limit Dynamic range ratio between lower and upper limits, usually in decibels (db for power and amplitude) e.g. voltage measurement from 1 mv to 20 V Note: similar to the acoustic amplitude (see lecture on signal processing) e.g. power measurement from 1 mw to 20 W P = U I = 1 U 2 R Note: 20 instead of 10 because square of voltage is equal to power!! [Adapted from Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

13 4a 4a - Perception - Sensors 13 General Sensor Performance Resolution minimum difference between two values usually: lower limit of dynamic range = resolution for digital sensors it is usually the A/D resolution. Linearity e.g. 5V / 255 (8 bit) variation of output signal as function of the input signal linearity is less important when signal is treated with a computer x f ( x) y f (y) α x + β y f ( α x + β y ) = α f ( x ) + β f ( y )? [From Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

14 4a 4a - Perception - Sensors 14 General Sensor Performance Bandwidth or Frequency the speed with which a sensor can provide a stream of readings usually there is an upper limit it depending di on the sensor and the sampling rate lower limit is also possible, e.g. acceleration sensor frequency response (see signal processing lecture): phase (delay) of the signal and amplitude might be ifl influenced [Adapted from Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

15 4a 4a - Perception - Sensors 15 In Situ Sensor Performance Characteristics that are especially relevant for real world environments Sensitivity ratio of output change to input change however, in real world environment, the sensor has very often high sensitivity to other environmental changes, e.g. illumination Cross-sensitivity (and cross-talk) sensitivity to other environmental parameters influence of other active sensors Error / Accuracy difference between the sensor s output and the true value error m = measured value v = true value [Adapted from Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

16 4a 4a - Perception - Sensors 16 In Situ Sensor Performance Characteristics that are especially relevant for real world environments Systematic ti error -> >deterministic i ti errors caused by factors that can (in theory) be modeled -> prediction e.g. calibration of a laser sensor or of the distortion cause by the optic of a camera Random error -> non-deterministic no deterministic i i prediction i possible however, they can be described probabilistically e.g. gaussian noise on a distance sensor, black level noise of camera Precision (different from accuracy!) reproducibility of sensor results σ = standard dev of the sensor noise [From Introduction to Autonomous Mobile Robots, Siegwart R. and Nourbakhsh I. R.]

17 Action - Actuators For different purposes: locomotion, control a part of the body y( (e.g., arm), heating, sound producing, etc. Examples of electrical-to-mechanical to actuators: DC motors, stepper motors, servos, loudspeakers, etc.

18 Computation Usually microcontroller-based; memory internal and potentially external to the microcontroller Discretization (analog-to-digital for values, continuous-to-discreteto for time) and continuization (digital-to-analog for values, discrete-to-continuous to continuous for time) Different types of control architectures: e.g., reactive ( reflex-based based ) vs. deliberative ( planning )

19 Microprocessors vs. Microcontrollers Microprocessors These chips contain a processing core, and occasionally a few integrated peripherals. In a broader sense, microprocessors are simply CPUs found in desktops. Microcontrollers These chips are all-in-one computer chips. They contain a processing core, memory, and integrated peripherals (e.g., ADC, motor control PWM generator, bus controller). In a broader sense, a microcontroller is a CPU that is used in an embedded system. stem

20 Communication Different physical channels: wired (e.g., RS232, USB) and wireless (e.g., radio, infrared, ultrasound, sound) Internal or external to the device: buses connecting different components (wired communication); external (node to base-station, node-to-node in a network) Asymmetric (one way) or symmetric (bidirectrional) link Direct (explicit) or indirect (implicit): direct implies dedicated hardware and software components for intentional, targeted information sharing; indirect, implies anonymous, broadcasting forms which are temporary (e.g., visual signs) or persist, perhaps with some volatility, in the environment (e.g., chemical signs such as pheromones)

21 Overview of Main Wireless Communication i Standards d Available for e-puck

22 Examples of Embedded Systems

23 Consumer Market Devices Digital Watch Weather station Digital camera Digital video camera

24 Niche Market Scientific Equipment Commercially Available e-puck Mica-Z Sensorscope station Handheld Airborne Mapping System

25 The e-puck miniature robot

26 Sl Selected tdand re-elaborated lb tdslides from: Microinformatique Introduction ti to the e-puck robot Francesco Mondada Robotics Systems Laboratory IMT - STI - EPFL

27 The e-puck Mobile Robot Main features Cylindrical, Ø 70mm dspic processor Two stepper motors Ring of LEDs Many sensors: Camera Sound IR proximity 3D accelerometer Li-ion accumulator Bluetooth wireless communication Open hardware (and software)

28 The e-puck Open Hardware License The specifications of the e-puck mobile robot are "open source hardware". You can redistribute them and/or modify them under the terms of the e-puck Robot Open Source Hardware License as published by EPFL. You should have received a copy of the EPFL e-puck Robot Open Source Hardware License along with these specifications; if not, write to the Ecole Polytechnique Fédérale de Lausanne (EPFL), Industrial Relations Office, Station 10, 1015 Lausanne, Switzerland. These specifications are distributed in the hope that they will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. For more details, see the EPFL e-puck Robot Open Source Hardware License.

29 Mechatronic Hardware Overview

30 Computation and memory Communication Actuators Sensors e-puck Block Schema

31 e-puck Overview IR receiver (remote control) Accelerometer Programming and debug connector ON-OFF microphones Wheels with stepper motor Speaker Reset Mode selector RS232 Ring of LEDs IR proximity i sensors CMOS camera Li-Ion accumulator

32 e-puck Mechanical Structure

33 e-puck Mechanical Structure

34 e-puck Mechanical Structure

35 e-puck Mechanical Structure

36 e-puck Mechanical Structure

37 e-puck Mechanical Structure

38 e-puck Mechanical Structure

39 e-puck Electronics (typical routing report produced by the EPFL PCB workshop)

40 e-puck kelectronics: Sample Schematics

41 e-puck Electronics: Placement of Components bottom top

42 e-puck Electronics: Layout (4 Layers PCB) mask top bottom mask inside

43 e-puck Electronics: e-jumper

44 On-Board Computational Capabilities

45 PIC/dsPIC Family from Microcontroller on the e-puck

46 DSP and Specialized Variants dspic is a family of chips combining microcontroller and Digital Signal Processor (DSP) structure and features For each dspic family member there are three variants: General purpose (codec interface) Motor control and power conversion (Pulse Width Modulation generator and encoder reading) Sensor processor (minimal variant)

47 dspic Family Variants e-puck e puck microcontroller

48 dspic Family Variants

49 dspic Architecture

50 Microcontroller core dspic Architecture

51 Memory and memory addressing dspic Architecture

52 Peripheral device control dspic Architecture

53 Peripheral Device Control ADC: Analog-to-Digital Converter SPI: Serial lperipheral linterface I 2 C: Inter-Integrated Circuit UART: Universal Asynchronous Receiver Transmitter CAN: Controller Area Network DCI: Data Converter Interface

54 16 channels, 12 bits Analog-to-Digital Converter (ADC)

55 Pinout dspic Architecture

56 Conclusion

57 Take Home Messages 1. Embedded system: specific purpose, equipped for interfacing discrete/digital and continuous/analog world, microcontroller-based design, often real-time constraints 2. Main modules of an embedded system: perception, action, computation, communication 3. e-puck use dspic as computational unit (programmable in C), has a reach sensory set, actuation capabilities, and bidirectional wireless and wired links 4. The hardware of an embedded device such an e-puck consists of a customized mechanical chassis and off-theshelf components (e.g., dspic, sensors, other logic chips, connectors, motors) assembled on one or several printed circuit boards (PCBs).

58 Additional Literature Week 7 Manuals and technical documentation MPLAB C30 C Compiler User s Guide dspic datasheet dspic30f Programmer s Reference Manual e-puck website: