1 / 18

Robotics - PowerPoint PPT Presentation

  • Updated On :

Robotics. R&N: ch 25. based on material from Jean-Claude Latombe, Daphne Koller, Stuart Russell. sensors. environment. ?. agent. effectors. Agent. Robots  Physical sensors and effectors. Sensors. Sensors that tell the robot position/change of joints: odometers, speedometers, etc.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Robotics' - oceana

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Robotics l.jpg


R&N: ch 25

based on material from Jean-Claude Latombe, Daphne Koller, Stuart Russell

Agent l.jpg







Robots  Physical sensors and effectors

Sensors l.jpg

  • Sensors that tell the robot position/change of joints: odometers, speedometers, etc.

  • Force sensing. Enables compliant motion--robot just maintains contact with object (video: compliant)

  • Sonar. Send out sound waves and measure how long it takes for it to be reflected back. Good for obstacle avoidance.

  • Vision systems

Effectors l.jpg

  • Converts software commands into physical motion

  • Typically electrical motors or hydraulic/pneumatic cylinders

  • Two main types of effectors:

    • locomotion

    • manipulation

Locomotion l.jpg

  • Legs!

    • traditional (video: honda human)

    • Other types

      • Statically stable locomotion: can pause at any stage during its gate without falling

      • Dynamically stable locomotion: stable only as long as it keeps moving (video: hopper)

  • Still, wheeled or tread locomotion like Shakey is still most practical for typical environments

  • Other methods: reconfigurable robots, fish robots, snake-like robots. (video: mod-robot)

Manipulation l.jpg

  • Manipulation of objects

  • Typical manipulators allow for:

    • Prismatic motion (linear movement)

    • Rotary motion (around a fixed hub)

  • Robot hands go from complex anthromorphic models to simpler ones that are just graspers

    • (video: manipulation)

    • (video: heart surgery)

Problems in robotics l.jpg
Problems in Robotics

  • Localization and Mapping

  • Motion planning

Localization where am i l.jpg
Localization: Where Am I?

  • Use probabilistic inference: compute current location and orientation (pose) given observations










Motion planning l.jpg
Motion Planning

  • Simplest task that a robot needs to accomplish

  • Two aspects:

    • Finding a path robot should follow

    • Adjusting motors to follow that path

  • Goal: move robot from one configuration to another

Configuration space l.jpg
Configuration space

  • Describe robot’s configuration using a set of real numbers

  • Flatland -- robot in 2D -- how to describe?

  • Degrees of freedom: a robot has k degrees of freedom if it can be described fully by a set of k real numbers

    • e.g. robot arm (slide)

  • Want minimum-dimension parameterization

  • Set of all possible configurations of the robot in the k-dimensional space is called the configuration space of the robot.

Example l.jpg

  • workspace for 2-D robot that can only translate, not rotate

  • configuration space describes legal configurations

    • free-space

    • obstacles

  • Configuration space depends on how big robot is—need reference point

Path planning l.jpg
Path planning

  • Goal: move the robot from an initial configuration to a goal position

  • path must be contained entirely in free space

  • assumptions:

    • robot can follow any path (as long as avoids obstacles)

    • dynamics are completely reliable

    • obstacles known in advance

    • obstacles don’t move

Assumption 1 l.jpg
Assumption #1

  • robot can follow any path

  • what about a car?

  • degrees of freedom vs. controllable degrees of freedom

    • holonomic (same)

    • nonholonomic

    • (video: holonomic)

Motion planning14 l.jpg
Motion planning

  • reduces to problem of finding a path from an initial state to a goal in robot’s configuration space

  • why is this hard?

Reformulate as discrete search l.jpg
Reformulate as discrete search

  • finely discretized grid

  • cell decomposition: decompose the space into large cells where each cell is simple, motion planning in each cell is trivial

  • roadmap (skeletonization) methods: come up with a set of major “landmarks” in the space and a set of roads between them

Issues in search l.jpg
Issues in Search

  • Complete

  • Optimality

  • Computational Complexity

Motion planning algorithms l.jpg
Motion planning algorithms

  • grid

  • cell decomposition

    • exact

    • approximate

  • roadmap (skeletonization) methods:

    • visibility graphs

    • randomized path planning

Robotics summary l.jpg
Robotics: Summary

  • We’ve just seen a brief introduction…

  • Issues:

    • sensors, effectors

    • Locomotion, manipulation

  • Some problems:

    • Localization

    • Motion Planning

  • Lots more!!