robotics “in which agents are endowed with physical effectors with which to do mischief” 1

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Robotics“In which agents are

endowed with physical effectors with which to do

mischief”1

1Russell and Norvig, Artificial Intelligence A Modern Approach, 2003, 901.

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?• Industrial Robots

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?

• Service Robots

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?

• Exploration

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?• Consumer Robots

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?

• Embedded Systems Programming– Cars, microwave

ovens, mobile phones

• Integrated Systems Engineering– Mechanical

Engineering– Electrical Engineering– Computer Science

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?

• Multitasking

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why Study Robotics?

• Its Fun!

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

What is An Intelligent Robot?

• A machine able to extract information from its environment and use knowledge about its world to move safely in a meaningful manner

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Humans vs. Robots

ProgramKnowledge

ComputerBrain

AC/DC PowerDigestion/Respiration

SensorsSenses

EffectorsMuscles

Mechanical StructureBones

RobotsPeople

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Robots vs. Softbots

• A softbot is a pure software agent whose environment consists of computer file systems, databases, and networks– Microsoft Office Helper, Game Agents, Web

Crawlers, Expert Systems

• Robot is an active, artificial agent whose environment is the physical world

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

The Real World is A Harsh Place

• Inaccessible– nearby stimuli, limited attention, imperfect

sensors

• Non-deterministic– Robot structure and dynamics, environment

• Dynamic– Changes happening as decisions are made

• Continuous– The world is not a set of discrete events

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Dealing with the Physical World

A robot needs to be able to handle its environment or the environment must be altered and controlled.

• Closed World Assumption– The robot knows everything relevant– no surprises– Reasonable only in very restricted domains

• Open World Assumption– The robot must be able to handle unexpected events.– The usual state of affairs

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

What does it take to get an intelligent robot to do a simple task?

Robot Parts: Two Arms, Vision, and Brain

The Brain can communicate with all parts

Arms can take commands as left, right, up, down, forward, and backward

Arms can answer yes/no about whether they are touching something but cannot distinguish what they are touching

The vision system can answer any question the brain asks, but cannot volunteer information.

The vision system can move around to get a better view.

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Why is this simple task so difficult?

• Coordination is difficult

• Indirect feedback

• Updating world knowledge

• Unexpected events– Need to re-plan

• Different coordinate systems need to be resolved– Box-centered and arm-centered

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Robot Control

• Two general approaches to controlling robot behavior:– Deliberative: reason about world, plan behaviors, act

• Human example: vacuum a room.

– Reactive: sense world, take action• Human example: pull hand away from a hot surface

• Hybrid approaches: combine both• Human example: ride a bike

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Deliberative/Hierarchical Robot Control

• Classic Robot Control, emphasizes planning• Basic paradigm is Sense -- Plan --Act• World knowledge must be represented in a form that

the robot can reason about.

Robot senses the world, constructs a model representation of the world, “shuts its eyes”, creates a plan of action, makes the action, then senses the results of the action.

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Deliberative: Good & Bad

• Goal Oriented– Solve problems that need cognitive abilities– Ability to optimize solution

• Predictable• Dependence on a world model

– Requires a closed world assumption– Symbol Grounding Problem– Frame Problem– Qualification Problem

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Reactive/Behavior-Based Paradigm

• Rodney Brooks 1987• Ignores world models• “The world is its own best model”• Sense -- act• Reactive Paradigm tightly couples perceptions

to actions– No intervening abstract representations or time

history

• Individual Behaviors are used as building blocks

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Where does the overall robot behavior come from?

• No overall goal, no planning• Emergent Behavior

– Emergence is the appearance of a novel property of a whole system that cannot be explained by examining the individual components, for example the wetness of water.

– Overall behavior is a result of robots interaction with its surroundings and the coordination between the individual behaviors.

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Reactive: Good & Bad• Works with the Open World Assumption

– Provides a timely response in a dynamic environment where the environment is difficult to characterize and contains a lot of uncertainty.

• Unpredictable• Low level intelligence

– Cannot manage tasks that require memory and higher level cognition

• Tasks requiring localization and order dependent steps

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Hybrid: Planning – Reactive Interaction

• Reactive in primary control and Planner provides advice– Planner configures the Reactive system

• Planner is primary and Reactive provides actions to avoid uncertain situations– Layered approach– Requires re-planning

• Planner and Reactive work concurrently

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Spectrum of Robot Control

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

Where are we with robotics?• AAAI robot competitions

– Robot Rescue– Robot Host– Robot Challenge

• Grace

• Lots of autonomous commercial applications• Some fairly impressive research• Beginning to see consumer applications• Barely at the beginning of applications which

involve interacting with humans

Derived from slides by Jerry Weinberg: http://www.cs.siue.edu/classes/Fall%202002/CS/CS490-CIS588/Weinberg/Lectures/

TODAY!Webcast: Artificial Intelligence for Autonomous Control in Space. Thurs, April 15, “PST” http://www.jpl.nasa.gov/events/lectures/apr04.cfm

A balloon-shaped robot explorer during a 70-kilometer wind-driven trek across Antarctica.

DARPA Desert race too tough for robots

NASA Mars Rovers Status 24 Mar 2004