1. CS 546: Intelligent Embedded Systems Gaurav S. Sukhatme Robotic Embedded Systems Lab Center for Robotics and Embedded Systems Computer Science Department University of Southern California gaurav@usc.edu http://robotics.usc.edu/~gaurav/CS546

2. Last Time Overview of the ENS box TinyOS tutorial Homework #2 No homework assigned today, nothing due next week

3. Today Memory Processor InterfaceSensor and actuator suite Energy supply External communication Platform OS and SW architecture Tools User interface Application Figure adapted from [Pottie and Kaiser 2005] 1/24, 4/18: Cyclops 1/31: Networking 2/21: Energy management 4/18: Cyclops 2/7,14 and 28: Time synch, localization and data management 3/21,28 and 4/11: Environmental monitoring

4. Sensors Basic principles Noise and figures of merit Types of sensors Calibration

5. Sensing Architecture Feedback transducer network Signal channel Transducer Analog signal procesing Digital signal processing A/D conversion Physical signal at source Physical signal at transducer Output signal

6. Sources of Noise Feedback transducer network Signal channel Transducer Analog signal procesing Digital signal processing A/D conversion Physical signal at source Physical signal at transducer Output signal

7. Figures of Merit Responsivity: output signal/input signal Sensitivity: (output signal without input)/(responsivity) Drift: slow change in output due to low- frequency noise Cross talk

8. Types of Sensors Environmental –Pressure, gas phase composition, automotive exhaust gas oxygen, Motion and force –Accelerometers, rotation and rotation rate, piezoresistive strain, microphone, capacitative position Electromagnetic transducers –Antennas, magnetometers, digital cameras. laser rangefinders Chemical and biochemical –Oxygen, nitrate (amperometric) Time –GPS

9. Transduction Principles Pressure – capacitance change Gas – absorption changes conductivity Accelerometer and rate gyros – proof mass displacement changes Microphone – diaphragm displacement changes resistance Piezoelectric – force changes polarization charge Magetometer – motion wrt coil induces a current Camera – photodetectors and CCD arrays Nitrate – use microfluidics to reduce an electrode and measure current

10. Types of Sensors Sensors range from simple to complex in the amount of information they provide – simple: an on/off switch (1 bit of input) – complex: the human retina (> 100 million photosensitive elements!) A sensor provides “raw” information, which usually needs to be processed

11. Sensor Complexity The output of a simple sensor can be used directly, without processing (e.g., if switch closed, stop, else go) The output of a complex sensor must be processed We can ask: “Given the sensory reading I am getting, what was the world like to make the sensor give me this reading?” => reconstruction

12. Signals -> Symbols (State) Sensors do not provide state/symbols, just signals A great deal of computation may be required to convert the signal from a sensor into useful state for the robot This process bridges the areas of electronics, signal processing, and computation

13. Levels of Processing to find out if a switch is open or closed, we need to measure voltage going through the circuit => electronics using a microphone to separate voice from noise and recognize => signal processing using a surveillance camera, find people in the image and recognize criminals, perhaps by comparing them to a large database => computation

14. Example: detecting people temperature: pyro-electric sensors detect special temperature ranges movement: if everything else is static or slower/faster color: if people wear uniquely colored clothing in your environment shape: now you need to do complex vision processing

15. Example: measuring distance ultrasound sensors (sonar) give you distance directly (time of flight) infra red provides return signal intensity two cameras (i.e., stereo) can give you distance/depth use perspective projection with 1 camera use a laser and a camera, triangulate use structured light; overlying grid patterns on the world...

16. Sensor Fusion A powerful strategy is to combine different sensors => Sensor Fusion Sensor fusion is complex because sensors have: – different characteristics – different accuracy – different complexity Computation is necessary to com-bine them effectively (in real-time)

17. Simple Sensors Can be used without much processing Still require electronics (and connectors) The basic electronics laws to know: – Ohm’s law – combining resistance – dividing voltage

18. Switch Sensors Switches are perhaps the simplest sensors of all They work without processing, at the electronics (circuit) level When a switch is open, no current can flow; when a switch is closed, current can flow (and be measured) This simple principle can (and is) used in a wide variety of ways

19. Uses of Switches Contact sensors: detect contact with another object (e.g., triggers when a robot hits a wall or grabs an object, whiskers, etc.) Limit sensors: detect when a mechanism has moved to the end of its range (e.g., triggers when a gripper is as open as it can be) Shaft encoder sensors: detect how many times a shaft turns (e.g., a switch clicks at every turn, clicks are counted)

20. Light Sensors Switches measure physical contact; light sensors measure the amount of light impacting a photocell Photocells are resistive sensors: the amount of light effects the amount of generated resistance Resistance is low when it is very light, high when it is dark Light sensors are really dark sensors!

21. Polarized Light Light waves traveling from a source emanate in all directions (with respect to the horizon) Polarized light waves travel only in a specific direction “Normal” light can be polarized by putting a filter in front of a light source The filter lets only the light waves of a given orientation (the characteristic plane) pass through

22. Polarized Light Sensors Filters can be combined to select various directions and amounts of light Polarized light can be used by placing polarizing filters: – at the output of a light source (emitter) – at the input of a photocell (receiver) Depending on whether the filters add (pass through) or subtract (block) the light, various effects can be achieved

23. Resistive Position Sensors Photocells are resistive devices, responding to light intensity Resistive devices can respond to various physical properties Bending is one such property, detected by resistive position sensors Originally developed for video game control (e.g., Nintendo Powerglove) Bending wears sensors out; less robust than other sensors

24. Potentiometers Potentiometers (a.k.a. pots) are everywhere Used for manual tuning of dials (radios, stereos, shaft encoders, etc.) The tuning adjusts the level of resistance in the circuit The device is a movable tap along two fixed ends (with fixed resistance). As the tap moves, resistance changes between the two extremes.

25. Active vs. Passive Sensors Passive sensors measure a physical property in the environment Active sensors provide their own signal/stimulus (and thus the associated source of energy) – reflectance – break-beam – infra red (IR) – ultrasound (sonar) –...

26. Reflective Optosensors The sensor consists of an emitter and a detector; two arrangements: Reflectance: emitter and detector are next to each other, separated by a barrier; light is reflected from objects back to the receiver Break-beam: emitter and detector face each other; objects interrupt the light from the emitter

27. Emitters and Detectors Emitters are usually made using light- emitting diodes (LEDs) Detectors are usually photodiodes/phototransistors Optosensors are not the same technology as resistive sensors Resistive sensors are simple but slow Optosensors are much faster

28. Reflectivity Properties Reflectivity depends on the color and other properties of a surface Lighter colors reflect better Black may not reflect at all (appears invisible) Lighter objects farther away seem closer than darker objects close by => The world is partially observable

29. Light Interference Ambient / background light can interfere with the sensor measurement It is best to subtract the ambient light level from the sensor measurement This is how: take two (or more, for increased accuracy) readings of the detector, one with the emitter on, one with it off, then subtract them This gives the ambient light level...

30. Sensor Calibration This process is called sensor calibration It provides the ambient light value to be subtracted from future sensor readings, to get the real measurement Of course ambient value can change, so calibration has to be repeated

31. Calibration Compare measurements to a reference Performed while manufacturing Tuning parameters (say a resistor) Need calibration methods in situ Usually non-linear interpolation

32. Break-Beam Sensors Any pair of compatible emitter-detector devices can be used to make a break- beam sensor Examples: – Incandescent flashlight bulb and photocell – Red LEDs and visible-light-sensitive photo- transistors – IR emitters and detectors

33. Shaft Encoders Shaft encoders measure the angular rotation of an axle They provide position and/or velocity Examples: – a speedometer measures the speed of the wheels – an odometer measures the number of rotations of the wheels

34. Disks for Counting Rotation To detect rotation, the turning element must somehow be marked Usually a round disk is attached to the shaft The disk has one or more notches cut in it A break-beam arrangement is set up: an emitter on one side of the disk, detector on the other

35. Counting Revolutions As a notch in the disk passes between the break-beam sensor, a rotation is detected and counted If the disk has only one notch, only complete rotations can be counted The more notches, the higher the resolution of the encoder If the shaft turns quickly, it is better to have higher resolution because...

36. Uses of Higher Resolution More notches allow for: – faster measurement – more accurate measurement (if there is noise/error) How else could we achieve shaft encoding without cutting notches?

37. Color-Based Encoders Instead of cutting notches, we can color the disk into alternating black and white wedges Then, instead of a break-beam mechanism, we need to set up a reflectance sensor: The emitter and detector are on the same side of the disk Black wedges absorb light, white reflect it => reflections are counted

38. General Encoder Properties Any encoder is an active sensor It produces and measures a wave function of light intensity The wave peaks are counted to compute the speed of the shaft Encoders measure position and rotational velocity (by subtracting the difference in the position after each reading) Where can encoders be used?

39. Signal De/Modulation We mentioned that ambient light is a source of interference in sensing Idea: emit modulated light (emitter is pulsed rapidly on and off) Use a demodulator to detect the signal at the particular pulse frequency The demodulator detector needs to measure several on-off flashes in a row to measure the frequency

40. Infra Red (IR) Sensors Infra red sensors work at a particular frequency of light (IR frequency) They are used in the same ways as the visible light sensors, but more robustly, to detect: – presence of objects – distance to objects Modulated IR is commonly used (e.g., remote controls)

41. Networking Often wireless, though not always Bluetooth, WiFi, adhoc variants, proprietary networking protocols Scaling based on logical and physical clustering

42. Network Self-Organization For large-scale embedded systems –Connectivity (topology) discovery – which links are possible, and which are desirable based on energy constraints –Channel assignments to avoid conflicts, subject to efficiency criteria –Connectivity maintanence

43. Topology Discovery Usually by hand shaking –One node issues an invitation on a predefined channel –Other nodes respond In wired networks – no energy constraint – receiver always on

44. Channel Assignments & Connectivity If some node knows the total number of nodes on the network, it can broadcast channel assignment In wireless networks – not clear if global connectivity is always possible given peak power constraints

45. Connectivity 100 node network – each node needs 7-9 neighbors to be fully connected Sharp transition from connected to not connected Control is via transmit power

46. Connectivity Issue invitations at max power –Listen to responses –Resolve contentions –Later abandon links during routing phase when shorter paths are discovered Issue invitations at low power –Capture ‘low-energy’ links –Grow as needed (vary duty cycle of invitation and response)

47. Routing Flooding –Never used globally, only local –Assumes links to neighbors are known Fixed directory –Brittle, efficient –Usually add redundancy for robustness Adaptive –Link-state: select short paths to update routes –Distance-vector: limit update packets to changes to a local routing table

48. Routing Shortest path: use shortest routes Demand driven: compute paths as needed Hierarchical: different methods at different levels (eg within cluster) Overlapping spanning trees Directed diffusion: flooding, response, reinforcement

49. Next time Time synchronization Read and critique papers before coming to class