Sensing self motion

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Sensing self motion

• Key points
• Why robots need self-sensing
• Sensors for proprioception
• in biological systems
• in robot systems
• Position sensing
• Velocity and acceleration sensing
• Force sensing
• Vision based proprioception

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Why robots need self-sensing

• For a robot to act successfully in the real world
  it needs to be able to perceive the world, and
  itself in the world.
• In particular, to control its own actions, it
  needs information about the position and movement
  of its body and parts.
• Our body contains at least as many sensors for
  our own movement as it does for signals from the
  world.

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Proprioception detecting our own movements

• To control our limbs we need feedback.
• Muscle spindles
• where length
• how fast rate of
• stretch
• Golgi tendon organ
• how hard force

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Proprioception Detecting our own movements

• To control our limbs we need feedback on where
  they are.
• Muscle spindles
• Golgi tendon organ
• Pressure sensors in skin

Pacinian corpuscle transient pressure response
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Proprioception (cont.)?

• To detect the motion of our whole body have
  vestibular system based on statocyst
• Statolith (calcium nodule) affected by gravity
  (or inertia during motion) causes deflection of
  hair cells that activate neurons

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Describing movement of body

• Requires
• Three translation components
• Three rotatory components

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Vestibular System Utricle and Saccule detect
linear acceleration.
Semicircular canals detect rotary acceleration in
three orthogonal axes
Fast vestibular-ocular reflex for eye
stabilisation
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For a robot

• Need to sense motor/joint positions with e.g.
• Potentiometer (current measures position)
• Optical encoder (counts axis turning)?
• Servo motor (with position feedback)?

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For a robot

• Velocity by position change over time or other
  direct measurement - tachometer
• E.g. using principal of dc motor in reverse
  voltage output proportional to rotation speed
• (Why not use input to estimate output?)?
• Acceleration could use velocity over time, but
  more commonly, sense movement or force created
  when known mass accelerates
• I.e. similar to statocyst

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Gyroscope uses conservation of angular momentum
Accelerometer measures displacement of weight
due to inertia
There are many alternative forms of these
devices, allowing high accuracy and
miniaturisation
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Inertial Navigation System (INS)?

• Three accelerometers for linear axes
• Three gyroscopes for rotational axes (or to
  stabilise platform for accelerometers)?
• By integrating over time can track exact spatial
  position
• Viable in real time with fast computers
• But potential for cumulative error

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For a robot

• Also want to sense force
• e.g.
• Strain gauge resistance change with deformation
• Piezoelectric - charge created by deformation of
  quartz crystal (n.b. this is transient)?

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For a robot

• Various other sensors may be used to measure the
  robots position and movement, e.g.
• Tilt sensors
• Compass
• GPS
• May use external measures e.g. camera tracking of
  limb or robot position.

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Some issues for sensors

• What range, resolution and accuracy are required?
  How easy to calibrate?
• What speed (i.e. what delay is acceptable) and
  what frequency of sampling?
• How many sensors? Positioned where?
• Is information used locally or centrally?
• Does it need to be combined?

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e.g. Haptic perception combines muscle touch
sense
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Vision as proprioception?

• An important function of vision is direct control
  of motor actions
• E.g. standing on one leg with eyes closed
• Standing up...

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The swinging room - Lee and Lishman (1975)?
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Optical flow
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Optical flow Heading focus of expansion
provided can discount flow caused by eye
movements
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Optical flow Flow on retina forward
translation eye rotation
Flow-fields if looking at x while moving towards
Bruce et al (op. cit) fig 13.6
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Optical flow time to contact
P distance of image from centre of flow
X distance of object from eye V velocity of
approach
Y velocity of P on retina
tau P/Y X/V rate of image expansion
time to contact
Lee (1980) suggested visual system can detect tau
directly and use to avoid collisions e.g. correct
braking.
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Using expansion as a cue to avoid collision is a
common principle in animals, and has been used on
robots

• E.g. robot controller based on neural processing
  in locust Blanchard et. al. (2000)?

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Summary

• Have discussed a variety of natural and
  artificial sensors for self motion
• Have hardly discussed how the transduced signal
  should be processed to use in control for a task.
  
• E.g. knowing about muscle and touch sensors
  doesnt explain how to manipulate objects

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Dimensions of robotics

• Defining goals Tasks or models
• Reaching goals programming or learning
• Reason or emotions
• Evaluation of performance
• Energy consumption
• Social issues
• Dynamical systems for control
• Design principles

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1. Biorobotics

• Robots as models of animal behaviour
• Proof of (functional) principle
• Bio-inspired robotics
• Biomorphic engineering
• Service robots
• Prosthetics
• Human-robot interaction

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2. Programming vs. Learning
O. Lebeltel, 1996
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2. Programming vs. Learning
O. Lebeltel, 1996
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Programming and Learning for control

• Action languages (R. Reiter)?
• Middleware concepts
• Machine learning methods
• Objective functions
• Self-organisation of behaviour
• Evolution and development
• Reinforcement learning

• Methods from
• Comp. Sc.
• Engineering
• Math
• Physics
• Biology
• Psychology

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The uncanny valley (Masahiro Mori, 1970)?

• Repliee Q1 and Geminoid
• (H. Ishiguro, U Osaka, 2005, 2007)?

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3. Emotion vs. Reason

• Emotions for robots
• Interaction with humans
• Internal evaluation
• Centralised supervision
• Kansei (emotion) engineering
• Reason for robots cf. 2. and previous lectures

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4. Performance Competition vs. Measurement

• DARPA Grand Challenge
• RoboCup Robot Soccer Rescue
• Climbing, underwater, fire fighting, ...
• RunBot Fastest robot on two legs
• Service limits, running costs, monitoring and
  support, flexibility, upgradability

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5. Energy consumption

• Super-human efficiency in certain tasks
• Inspiration from biology Passive dynamics in
  walking, energy re-use by springs, locking
  mechanisms for posture maintenance, modularity,
  hibernation
• Development of enduring batteries
• Alternative energies Solar robots
• Fly-eating robot (UWE, 2004)?

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6. Social robots

• Division of labour, specialised hardware
• Communication, cooperation, collaboration
• Collaboration gain (super-linear increase with
  number of robots?)?
• Understanding language and social behavior
• Swarms intelligence from many very simple robots
• Human-Robot workgrounps

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7. Dynamical systems vs. control

• Closed perception-action loop
• Everything is in the senses
• Evolution
• No planning, no representation
• Exploratory
• Potentially interesting

• Feed-forward, feed-back
• Objective-driven, uses prior knowledge
• Design
• Planning reqired for complex goals
• Dependability
• Potentially useful

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8. Distributed vs. centralized

• Modularity on all levels
• Re-configurability
• Fast local computations
• Communication partially replaced by local
  decisions
• Bio-inspired solutions

• Monitoring
• Simplicity
• Debugging
• Communication less demanding

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9. Areas of applications

• Assembly, manufacturing, manipulation
• Remote operation, exploration, rescue
• Science and education
• Prosthetics, orthotics, surgery, therapy
• Service, transport, surveillance
• Entertainment, toys, sports
• Military

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More dimensions as discussed before

• Vision
• Sensing and Acting
• Locomotion, reaching and grasping
• Dynamics and kinematics
• Control
• Internal organization, architectures

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