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Robotic. Chapter 7. Robotic. 1) Robotics is the intelligent connection of perception action. 2) A robotic is anything that is surprisingly (moving target) animate. 3) perceptual (S/W) + motor task (H/W) [action] operate in the real world : searching and backtracking can be costly

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robotic

Robotic

Chapter 7

robotic1
Robotic

1) Robotics is the intelligent connection of perception action.

2) A robotic is anything that is surprisingly (moving target) animate.

3) perceptual (S/W) + motor task (H/W) [action]

  • operate in the real world : searching and backtracking can be costly
  • we need operating in a simulate world with full information for an optimal plan by best-first search
  • we can checked preconditions of the operators using perception to perform action
  • real time search : p. 562 A* algorithm, RTA* (Korf 1988)

Chapter 7 Robotic

vision
Vision

2D  3D

signal processing : enhance the image

measurement analysis : for image containing a single object determining the 2D extent of the object depicted

pattern recognition : for single object images, classify the object into category

image understanding : for image containing many objects in the image, classify them, build 3D model of the scene. see Figure 14.8 p. 367

Chapter 7 Robotic

slide4

Vision

  • Problem :
  • ambiguous image : see Figure 21.2 p. 564
  • Figure 21.3 p. 565 using low level knowledge to interpret an image
  • image factor, sensor fusion : color, reflectance, shading
  • Figure 21.4 p. 565 using high level knowledge to interpret an image (a) use surroundings objects to help (b) baseball, log in a fireplace, amoeba, [egg, bacon, and plate]
  • Figure 21.5 p. 567 Image understanding
  • analog signal Image 2D features 3D features
  • 3D composite objects Object identification

Chapter 7 Robotic

speech recognition
Speech Recognition
  • speaker dependence (we can train the system) / speaker independence
  • continuous / isolated word speech
  • real time SPHINX (1988) / offline processing
  • large (difficult) / small vocabulary
  • broad (difficult) / narrow grammar: TANGORA (1985) 20000 words vocabulary
  • HMM (Hidden Markov Modeling) SPHINX system
    • statistical learning method
    • HMM is a collection of states and transitions

Chapter 7 Robotic

speech recognition1
Speech Recognition

HMM (Hidden Markov Modeling) SPHINX system

statistical learning method

HMM is a collection of states and transitions

the problem of decoding a speech waveform turns into the problem of finding the most likely path (set of transitions) through an appropriate KMM.

Chapter 7 Robotic

action
Action
  • p. 569 : navigation around the world
  • planning routes / path planning
  • reaching desired destinations without bumping into things
  • see Figure 21.6–21.9 p. 570-571
  • constructing a visibility graph
  • configuration space / C-space (Lozano-Perez 1984)
    • basic idea is to reduce the robot to a point P and do path planning in an artificially constructed space
    • rotation (X,Y,)
  • obstacles can be transformed into 3D C-space objects, visibility graph can be created and searched.

Chapter 7 Robotic

manipulation
Manipulation
  • end-effectors (two-gripper) / a human like hand
  • pick-and-place : grasp and object and move it to a specific location see Figure 21.10-21.11 p. 572-573
  • Figure 21.11-21.12 (a) naive strategy for grasping and placement
  • Figure 21.11-21.12 (b) clever strategy for grasping and placement
  • planning p. 332 e.g. Block world ON(A,B) HOLDING , ARMEMPTY

Chapter 7 Robotic

manipulation1
Manipulation
  • planning p. 332 e.g. Block world ON(A,B) HOLDING , ARMEMPTY
  • Components of a planning system

1) choose the best rule to apply

2) applying rules see Figure 13.2-13.3 p. 336-337

3) detecting a solution

4) detecting dead ends

5) repairing an almost correct solution

Chapter 7 Robotic

slide10

The End

Chapter 7 Robotic