Mobile Robotics

Robot HardwareNon-visual Sensors

Overview

Sensor introduction sensor characteristics sensor types

Types of sensor General classification:

contact vs non-contact active vs passive sampling rate: fast vs slow local vs non-local

Specific examples touch close-range proximity infrared sonar laser (various types) vision radar compasses, gyroscopes

Robot Sensors Sensors are devices that can sense and measure

physical properties of the environment, • e.g. temperature, luminance, resistance to touch, weight,

size, etc.• The key phenomenon is transduction.

They deliver low-level information about the environment the robot is working in.

This information is noisy (imprecise) and, as a result, often difficult to interpret.

What does it mean to interpret the sensor?

Sensors Objectives & goals from sensing: what do we

want? Who's we, the researcher?

Consider the following: Task Generic capability Measured primitive (e.g intrinsic image [Marr, 1980]) Measurement process Sensor

-- suggestions… for tasks and what we need

Answers… Tasks:

Vacuuming (a la romba), Creating of web tours of an art gallery,

Warehouse surveillance,

Mail delivery, Hospital food delivery,

Mine sweeping on land, Mine sweeping in the water,

Automotive convoy behavior,

Mars exploration,

Capabilities Mapping,

Pose estimation

Path planning navigation, coverage, collision avoidance target detection,

Primitives: Range maps

Reflectance maps,

Sensor CharacteristicsAll sensors are characterized by various properties that describe their

capabilities Sensitivity: (change of output) ÷ (change of input) [high] Linearity: constancy of (output ÷ input) [yes] measurement range: difference between min. and max. [large] response time: time required for a change in input to cause a

change in the output [low] Accuracy:difference between measured & actual [high] Repeatability: difference between repeated measures [high] Resolution: smallest observable increment [high==small] Bandwidth: result of high resolution or cycle time [high]

Sensor Types Most sensing is described with reference to

biological organisms. What kinds of sensing can you imagine?

What creatures use it,and has it been tried in robotics?

There are many different types of sensor many sense phenomena that humans cannot detect

e.g. magnetism, infra-red, ultra-violet, ultrasound,phase of light (e.g. polarised sun-glasses), etc.

Active v. Passive Sensors can be broadly classified as either active (energy

emitting) or passive (using energy that's "already out there"). Active is more "costly", but usually entails a simpler inverse

problem and entails fewer assumtions about the environment. active

radiating some form of energy into the environment e.g.

radar (radio direction and ranging)sonar (sound navigation and ranging)lidar (light direction and ranging)

passive relying on energy emitted by various objects in environment

Vision Ubiquitous. Why so popular? Strengths and weaknesses.

The sensor. The interpretation.

Sensors• Proprioceptive  Sensors        (monitor  state  of  robot)

– IMU  (accels  &  gyros)– Wheel  encoders

• Exteroceptive  Sensors        (monitor  environment)

– Cameras  (single,  stereo,  omni,  FLIR  …)

– Laser  scanner– MW  radar– Sonar  – Tactile…

Sensor Detail

Interaction 2

Q. Ask students to consider the problem of navigating a small mobile robot from one side of the classroom to the other, whilst avoiding obstacles

What sort of sensors are required?

A. Almost certainly a combination, e.g.:

laser + few backup ultrasonicshigh density ultrasound array

laser + cheap light sensor[optionally to all: bump sensor(s) as fail-safe]

There are many different technologies e.g. contact closure, magnetic, piezoelectric, etc.

Vibrassae/whiskers of rats Surface texture information. Distance of deflection. Blind people using a cane.

For mobile robots these can be classed as tactile feelers (antennae) often some form of metal wire passing through a wire loop -

can be active (powered to mechanically search for surfaces) tactile bumpers

solid bar / plate acts on some form of contact switche.g. mirror deflecting light beam, pressure bladder, wire loops, etc.

distributed surface arraysminiature switches are arranged in a 2D array to provide shape information and

sometimes pressure (as skin)

Tactile Sensors

Proximity Sensors Tactile sensors allow obstacle detection

proximity sensors needed for true obstacle avoidance Several technologies can detect the presence of particular

fields without mechanical contact magnetic reed switches

two thin magnetic strips of opposite polarity not quite touching an external magnetic field closes the strip & makes contact

Hall effect sensors small voltage generated across a conductor carrying current

inductive sensors, capacitive sensors inductive sensors can detect presence of metallic objects capacitive sensors can detect metallic or dielectric materials

Infrared Sensors Infrared sensors are probably the simplest type of non-

contact sensor widely used in mobile robotics to avoid obstacles

They work by emitting infrared light

to differentiate emitted IR from ambient IR (e.g. lights, sun, etc.), the signal is modulated with a low frequency (100 Hz)

detecting any reflections off nearby surfaces In certain environments, with careful calibration, IR sensors

can be used for object distance requires uniform surface colours and structures

Infrared Problems If the IR signal is detected, it is safe to assume that an object

is present However, the absence of reflected IR does not mean that no

object is present! certain dark colours (black) are almost invisible to IR IR sensors are not absolutely safe for object detection

In realistic situations (different colours & types of objects) there is no accurate distance information it is best to avoid objects as soon as possible

IR are short range typical maximum range is 50 to 100 cm

Infrared  Sensors  (Sharp)

• Measures  the  return  angle  of  the  infrared  beam.

Sonar Sensors

The fundamental principle of robot sonar sensors is the same as that used by bats emit a chirp (e.g. 1.2 milliseconds)

a short powerful pulse of a range of frequencies of sound its reflection off nearby surfaces is detected

As the speed of sound in air is known (≈ 330 m·s-1) the distance to the object can be computed from the elapsed time between chirp and echo minimum distance = 165 tchirp (e.g. 21 cm at 1.2 ms) maximum distance = 165 twait (e.g. 165 m at 1 s)

Usually referred to as ultrasonic sensors

Sonar Problems There are a number of problems and uncertainties associated

with readings from sonar sensors it is difficult to be sure in which direction an object is

because the 3D sonar beam spreads out as it travels specular reflections give rise to erroneous readings

the sonar beam hits a smooth surface at a shallow angle and so reflects away from the sensor

only when an object further away reflects the beam back does the sensor obtain a reading - but distance is incorrect

arrays of sonar sensors can experience crosstalk one sensor detects the reflected beam of another sensor

the speed of sound varies with air temp. and pressure a 16° C temp. change can cause a 30cm error at 10m!

Laser Range Finders Laser range finders commonly used to measure the distance,

velocity and acceleration of objects also known as laser radar or lidar

The operating principle is the same as sonar a short pulse of (laser) light is emitted the time elapsed between emission an detection is used to

determine distance (using the speed of light) Due to the shorter wavelengths of lasers, the chance of

specular reflections is much less accuracies of millimetres (16 - 50mm) over 100m 1D beam is usually swept to give a 2D planar beam

May not detect transparent surfaces (e.g. glass!)

Laser based ranging In addition to LIDAR (Time Of Flight: TOF)

methods, there are also laser triangulation systems.

These used geometric methods to infere distance. They are essentially active-vision-based variations of

stereo vision systems or line striping. As such, they will be discussed under "vision".

RADAR Radar usually uses electromagnetic energy in the 1 - 12.5

GHz frequency range this corresponds to wavelengths of 30 cm - 2 cm

microwave energy unaffected by fog, rain, dust, haze and smoke

It may use a pulsed time-of-flight methodology of sonar and lidar, but may also use other methods continuous-wave phase detection continuous-wave frequency modulation

Continuous-wave systems make use of Doppler effect to measure relative velocity of the target

Angular  Posi6on:  Rotary  Encoder• Potentiometer

– Used  in  the  Servo  on  the  boebots• Optical  Disks  (Relative)

– Counting  the  slots– Direction  by  having  pars  of  emitters/receivers  out  of  phase:  Quadrature  decoding

– Can  spin  very  fast:  500  kHz

Angular  Posi6on:  Rotary  Encoder

• Optical  Disks  (Absolute)– Grey  encoding  for  absolute:

•  0:0000,    1:1000,    2:1100,    3:0100,    4:0110,•  5:1110,    6:1010,    7:0010,    8:0011•  9:1011,  10:1111,  11:0111,  12:0101,  13:1101,  14:1001,  15:0001

Compass Sensors Compass sensors measure the horizontal component of the

earth’s magnetic field some birds use the vertical component too

Typically some form of (2D) gimbal and fluid suspension is used to reduce pitch-and-roll not usually totally accurate for land-based vehicles

The earth’s magnetic field is very weak indoors there are likely to be many other field sources

steel girders, reinforced concrete, power lines, motors, etc. an accurate absolute reference is unlikely, but the field is approx.

constant, so can be used for local reference

Gyroscopes

A gyroscope is a spinning wheel with most of its mass concentrated in the outer periphery e.g. a bicycle wheel

Due to the law of conservation of momentum the spinning wheel will stay in its original orientation a force is required to rotate the gyroscope

A gyro. can thus be used to maintain orientation or to measure the rate and direction of rotation

In fact there are different types of mechanical gyro. and even optical gyro’s with no moving parts!

these can be used in e.g. space probes to maintain orientation

Vibra6ng  Structure  Gyroscopes

Halteres

MEMS

ring gyro's Use standing waves set up

between mirrors (laser ring gyro) within a fiber optic cable (fribre optic ring gyro)

Measure rotation by observing beats in standing wave as the mirrors "rotate through it".

IMU's Gyro, accelerometer

combination. Typical designs (e.g. 3DM-

GX1™) use triaxial gyros to track dynamic orientation and triaxial DC accelerometers along with the triaxial magnetometers to track static orientation.

The embedded microprocessors contains a programmable filter algorithms, which blends these static and dynamic responses in real-time.

Odor sensingSmell is ubiquitous in nature… both as a active and a passive sensor. Why is it so important?

Advantages: evanescent, controllable, multi-valued, useful.

References: A. T. Hayes, A. Martinoli, and R. M. Goodman. Swarm Robotic Odor Localization:

Off-Line Optimization and Validation with Real Robots. Special issue on Biological Robotics, D. McFarland, editor, Robotica, Vol. 21, Issue 4, pp. 427-441, 2003. © Cambridge University PressB. T. Yamanaka, R. Matsumoto, and T. Nakamoto,

"Fundamental study of odor recorder for multi-component odor using recipe exploration method based on singular value decomposition", IEEE Sensors Journal, Vol. 3, Issue 4, 2003, pp. 468-474.

Odor: how many values? Mamallian system:

olfactory bulb: ~50 million sensors population coding for specific labels

Typical artificial sensor: 20 to 50 sensors optical or DNA-chip mechanism can be small, remote for main computer

Applications: toxicology, industrial processes, security, food processing,

medicine, environmental assessment.

Population code: learning needed

Nature , 382: 697-700 (1996).

Now, an idealized sensing algorithm The art gallery problem.

Nice bound. What makes it hard to use?

The Art Gallery Problem

camera

How many cameras are needed to guard a gallery and How should they be placed?

Simple Polygon ModelModel the art gallery as a region bounded by some simple polygon (no self-crossing).

Regions with holes are not allowed.

convex polygonone camera an arbitrary n-gon (n vertices)

Bad news: finding the minimum number of cameras for a given polygon is NP-hard (exponential time).

TriangulationTo make things easier, we decompose a polygon into pieces that areeasy to guard.

Draw diagonals between pair of vertices.

an open line segment that connects two vertices and lie in the interior of the polygon.

Triangulation: decomposition of a polygon into triangles by a maximal set of non-intersecting diagonals.

Guard the polygonby placing a camera in every triangle …

# TrianglesTheorem 1 Every simple polygon has a triangulation. Any triangulation of a simple polygon with n vertices consists of exactly n – 2 triangles.

Proof By induction.

Trivial for n = 3. Assume true for all m < n.

Existence

Let v be the leftmost vertex and u and w its two neighbors.

• uw in the interior of P ⇒ it is a diagonal.

u

vw P

vw

uvʹ′

• Otherwise, the triangle determined by u, v, w contains at least one vertex. Let vʹ′ be the one closest to v. Then vvʹ′ is a diagonal.

The diagonal splits the polygon into two (which by induction can be triangulated).

Proof (cont’d)

Any diagonal splits P into two simple polygons with k and m vertices, respectively.

# triangles = n – 2

By induction these two subpolygons can be triangulated.They are decomposed into k – 2 and m – 2 triangles, resp.

Vertices defining the diagonal occur in each subpolygon once.

Other vertices of P each occurs in exactly on one subpolygon.

Thus k + m = n + 2.

By induction, the triangulation of P has (k – 2) + (m – 2) = n – 2 triangles.

# Cameras for AG

Theorem 1 ⇒ n – 2 cameras can guard the simple polygon.

A camera on a diagonal guards two triangles.

⇒ # cameras can be reduced to roughly n/2.

A vertex is adjacent to many triangles. So placing cameras at vertices can do even better …

3-Coloring Idea: Select a set of vertices, such that any triangle has at least one selected vertex.

Assign each vertex a color: pink, green, or yellow.

Any two vertices connected by an edge or a diagonal must be assigned different colors.

Thus the vertices of every trianglewill be in three different colors.

If 3-coloring exists, place cameras at all vertices of the same color.Choose the smallest color class to place the cameras. ⇒ ⎣n/3⎦ cameras.

The Dual GraphDual graph G has a node inside every triangle and an edge between every pair of nodes whose corresponding triangles share a diagonal.

Any diagonal cuts the polygon into two.

Thus the dual graph is a tree. ⇒

Every diagonal corresponds to an edge in the dual graph. Removal of any edge from the dual graph disconnects it.

G is connected.

A 3-Coloring AlgorithmA 3-coloring can be found through a graph traversal (such as DFS).

During DFS, maintain the invariant:

All polygon vertices of encounteredtriangles have been colored such thatno adjacent two have the same color.

Start DFS at any node of G.Color the three vertices of the corresponding triangle.

v

u

Suppose node v is visited from u.

⇒

⇒ Their triangles T(v) and T(u) are adjacent.

Only one vertex of T(v) is not colored. ⇒ Its color is uniquely determined.

Since G is a tree, the other nodes adjacent to v have not been visited yet.Otherwise there exists a cycle (which contradicts that G is a tree.)Apply the color to v.

A Worst CaseA triangulated polygon can always be 3-colored.

⇒ Any simple polygon can be guarded with ⎣n/3⎦ cameras.

⎣n/3⎦ prongs

There exists no position at which a camera can oversee two prongs.

⎣n/3⎦ cameras are needed.

The 3-coloring approach is optimal in the worst case.

Art Gallery TheoremFor a simple polygon with n vertices, ⎣n/3⎦ cameras are sufficient to have every interior point visible from at leastone of the cameras.

Solution to the Art Gallery Problem

1. Triangulate a simple polygon with a fast algorithm.

DCEL representation for the simple polygon so we can visit a neighbor from a triangle in constant time.

2. Generate a 3-coloring by DFS (as presented earlier).

3. Take the smallest color class to place the cameras.

DCEL stands for Doubly-Connected Edge List. A DCEL is a data structure for efficiently storing topological information about a 2D surface (Possibly located in 3D space). The surfaces so represented are usually considered to be equivalent to planar subdivisions, although not every implementation will necessarily be able to store a true planar subdivision.

Discussion The art gallery problem.

Concerns in practice?