16.412J/6.835 Intelligent Embedded Systems

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16.412J/6.835 Intelligent Embedded Systems

• Prof. Brian Williams
• Rm 37-381
• Rm NE43-838
• Williams_at_mit.edu

MW 11-1230, Rm 33-418
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Outline

• Course Objectives and Assignments
• Types of Reasoning
• Kinds of Intelligent Embedded Systems
• A Case Study Space Explorers

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Course Objective 1

• To understand fundamental methods for creating
  the major components of intelligent embedded
  systems.
• Accomplished by
• First ten lectures on basic methods
• 5 problem sets during the first ten lectures to
  exercise basic understanding of methods.

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Basic Method Lectures

• Decision Theoretic Planning
• Reinforcement Learning
• Partial Order Planning
• Conditional Planning and Plan Execution
• Propositional Logic and Inference
• Model-based Diagnosis
• Temporal Planning and Execution
• Bayesian Inference and Learning
• More Advanced
• Graph-based and Model-based Planning
• Combining Hidden Markov Models and Symbolic
  Reasoning

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Course Objective 2

• To dive into the recent literature, and
  collectively synthesize, clearly explain and
  evaluate the state of the art in intelligent
  embedded systems.
• Accomplished by
• Weekly thought questions ( 2 page answers)
• Group lecture on advance topic
• 45 minute lecture
• Short tutorial article on method 1-3 methods
• Demo of example reasoning algorithm
• Groups of size 3.

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Course Objective 3

• To apply one or more reasoning elements to create
  a simple agent that is driven by Goals or
  Rewards
• Accomplished by
• Final project during last third of course
• Implement and demonstrate one or more reasoning
  methods on a simple embedded system.
• Short final presentation on project.
• Final project report.

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Outline

• Course Objectives and Assignments
• Types of Reasoning(Slides compliments of Prof
  Malik, Berkeley)
• Kinds of Intelligent Embedded Systems
• A Case Study Space Explorers

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Agents and Intelligence
Prof Malik, Berkeley
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Reflex agents
Compliments of Prof Malik, Berkeley
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Reflex agent with state
Compliments of Prof Malik, Berkeley
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Goal-oriented agent
Compliments of Prof Malik, Berkeley
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Utility-based agent
Compliments of Prof Malik, Berkeley
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Outline

• Course Objectives and Assignments
• Types of Reasoning
• Kinds of Intelligent Embedded Systems
• A Case Study Space Explorers

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Immobile Robots Intelligent Offices and
Ubiquitous Computing
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Ecological Life SupportFor Mars Exploration
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courtesy NASA
The MIR Failure
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Portable Satellite Assistant
courtesy NASA Ames
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MIT Spheres
courtesy Prof. Dave Miller, MIT Space Systems
Laboratory
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courtesy JPL
Distributed Spacecraft Interferometers to search
for Earth-like Planets Around Other Stars
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A Goldin Era of Robotic Space Exploration
courtesy JPL
Our vision in NASA is to open the Space
Frontier . . . We must establish a virtual
presence, in space, on planets, in aircraft and
spacecraft. - Daniel S. Goldin, NASA
Administrator, May 29, 1996
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Cooperative Exploration
Distributed Planning Group, JPL
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MIT Model Based Embedded and Robotics Group
Autonomous Vehicles Testbed
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Robotic Vehicles

• ATRV Rovers
• Monster Trucks
• Blimps
• Spheres
• Simulated Air/Space Vehicles

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Indoor test range

• Aim Scope
• indoor experiments for target site exploration
• cooperative exploration

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Scenario
Cooperative Target Site Exploration Heterogeneous
rover team and blimps explore science sites
determined by remote sensing

• Tasks
• small scout rovers (ATRV Jr) explore terrain as
  described in earlier scenarios
• blimps provide additional fine grain air
  surveillance
• scout rovers identify features for further
  investigation by sample rover (ATRV)
• scout rovers provide refined terrain mapping for
  path planning of the larger sample rover
• Scenario Research Objective
• Extend coordination to heterogeneous team

exploration region identified feature goal
position
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Cryobot Hydrobot
Exploring life under Europa
courtesy JPL
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Outline

• Course Objectives and Assignments
• Types of Reasoning
• Kinds of Intelligent Embedded Systems
• A Case Study Space Explorers

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A Capable Robotic Explorer Cassini

• 7 year cruise
• 150 - 300 ground operators
• 1 billion
• 7 years to build

Cassini Maps Titan
courtesy JPL
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courtesy JPL
Our vision in NASA is to open the Space
Frontier . . . We must establish a virtual
presence, in space, on planets, in aircraft and
spacecraft. - Daniel S. Goldin, NASA
Administrator, May 29, 1996
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Four launches in 7 months
Mars Climate Orbiter 12/11/98
Mars Polar Lander 1/3/99
QuickSCAT 6/19/98
Stardust 2/7/99
courtesy of JPL
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• Vanished
• Mars Polar Lander
• Mars Observer

courtesy of JPL
Spacecraft require commonsense
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Traditional spacecraft commanding
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Houston, We have a problem ...

• Quintuple fault occurs (three shorts, tank-line
  and pressure jacket burst, panel flies off).
• Mattingly works in ground simulator to identify
  new sequence handling severe power limitations.
• Mattingly identifies novel reconfiguration,
  exploiting LEM batteries for power.
• Swaggert Lovell work on Apollo 13 emergency rig
  lithium hydroxide unit.

courtesy of NASA
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Self Repairing Explorers Deep Space 1