CS 326 A: Motion Planning

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CS 326 A Motion Planning

• http//robotics.stanford.edu/latombe/cs326/2002
• Planning Exploration Strategies

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Exploration ? Map Building

• A robot is introduced in a new environment
• Its task is to build a model (2D or 3D) of this
  environment
• It goes from place to place.
• At each place it acquires a local model that it
  merges with the current global model

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Example
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Example
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Localization Issue

• Initial position of the robot ? reference
  coordinate frame
• Dead-reckoning (e.g., odometry) yields increasing
  errors
• ? Need to match each new local model with current
  global model (correspondence problem)

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Correspondence Problem
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Localization Issue

• Initial position of the robot ? reference
  coordinate frame
• Dead-reckoning (e.g., odometry) yields increasing
  errors
• ? Need to match each new local model with current
  global model
• ? Simultaneous Localization and Mapping (SLAM)

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Loop Issue
Loops ? Complex optimization problem (incrementali
ty vs. global optomization)
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Not a New Issue!
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Two Sub-problems in Exploration

• Where to go next?
• - Maximize amount of new information
• - Ensure minimal model overlap
• - Minimize travel length
• ? Next-best view
• How to best merge the two models?
• - Minimize expected errors Kalman filtering,
  expectation maximization (most likely map)

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Other Exploration Issues

• Map model polygonal, occupancy grid, topological
  network, 3D surfaces, object map, etc
• Moving objects
• Meaning of objects
• Multiple robots
• Unstructured environments

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Other Exploration Issues

• Map model polygonal, occupancy grid, topological
  network, 3D surfaces, object map, etc
• Moving objects
• Meaning of objects
• Multiple robots
• Unstructured environments