Mobile Robot Control Architectures

1
Mobile Robot Control Architectures

• A Robust Layered Control System for a
• Mobile Robot -- Brooks 1986
• On Three-Layer Architectures -- Gat 1998?
• Presented to CS547
• September 29, 1999
• Jeremy Elson

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mobile robot controllers

• The brains behind a mobile, autonomous robot
  (using the lite definition of autonomous)
• Even though the controller is sometimes not
  physically on the robot
• Well talk about
• The Old School Sense-Plan-Act
• The Brooks School Subsumption
• The Modern School Three-Layer

3
a typical robot
Processor
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sense - plan - act

• Consists of 3 linear, repeated steps
• Sense your environment
• Plan what to do next by building a world model
  through sensor fusion, and taking all goals into
  account -- both short term and long term
• Execute the plan through the actuators
• The predominant robot control mechanism through
  1985

5
robots have many goals
I need to inspect these railroad spikes
I want to take a nap
A train is about to hit me
I am about to fall over
I just want to be loved
A goals priority naturally will change based on
context
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slicing the problem spa
All goals are known at each stage, and affect the
computation
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problems with spa(sense-plan-act)

• Its monolithic design makes it slow
• At each step, we have to do sensor fusion, world
  modeling, and planning for all goals
• Slow means we almost never can plan at the rate
  the environment is changing
• We end up doing open-loop plan execution -
  inadequate in the fact of uncertainty and
  unpredictability

8
new architecturesubsumption

• Introduced in Brooks seminal 1986 paper
• Consists of layered behaviors, from simple to
  complex, with simple interfaces
• Layers can override each other
• Each layer has a control program that is capable
  of working at the speed of environmental change
• Each layer now can do the appropriate model
  building, sensor fusion, etc.

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slicing the problem subsumption
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subsumption details

• Each layer has one function, conceptually
• Lower layers tend to be more reactive
• closed loop controls
• inputs tightly coupled to outputs
• Higher layers are more deliberative
• do higher-level sensor fusion modeling
• keep more state
• planning further in the future
• Layers can fake the inputs or outputs of other
  layers

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subsumption advantages(according to brooks)

• Provides a way to incrementally build and test a
  complex mobile robot control system
• Supports parallel computation in a
  straightforward, intuitive way
• Avoids centralized control relies on
  self-centered and autonomous modules
• Leads to more emergent behavior -- Complex (and
  useful) behavior may simply be the reflection of
  a complex environment
• Compare with SPA - intelligence is entirely in
  the design of the planner (the programmer)

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subsumption successes

• Brooks originally implemented
• Level 0, object avoidance
• Level 1, wandering
• Level 2, explore (simulated only)
• Early efforts were a dramatic success, zipping
  around like R2D2 instead of pondering their plans
• Pinnacle (according to Gat) was Herbert, who
  found soda cans in an office

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...and failures?

• Herbert didnt work very repeatably
• According to Gat, no subsumption-based robot
  since Herbert -- or is there?
• Is classical subsumption still in use?
• Gat says Cog is based on subsumption
• Brooks publications, however, mainly describe
  imitation of human cognitive models and do not
  explicitly mention subsumption
• But, these models also stress non-monolithic
  control subsumption might be there implicitly

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three-layer architectures

• Response to subsumption, simultaneously and
  independently developed by gt3 groups
• TLA design seems to implicitly
• Agree that different processing models are needed
  to react to events on different time scales
• Agree with loose asynchronous interfaces
• Disagree with the infinite regression of layers
• Disagree with the subsumption mechanism itself --
  i.e. overriding of inputs/outputs
• But is this the essence of subsumption?

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the role of state

• SPA
• Uses extensive internal state
• Plans slowly and infrequently
• Gets into trouble when its internal state loses
  sync with the world
• Reactive
• The World is its Own Best Model
• No internal state
• Tight sensor to actuator coupling
• Runs headlong into the problem of extracting
  state information from the world using sensors
• Hybrid/Three Layer
• Cant we all just get along?

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the three-layer architecture

• Consists of (surprise!) 3 layers
• Reactive layer (Controller)
• Stateless, sensor-based
• Short time scale actions
• Glue Layer (Sequencer)
• Has a memory of the past
• Selects primitive behaviors for Controller
• Planning Layer (Deliberator)
• Plans for the future
• Time-consuming operations (search, complex
  vision, etc.)

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what is subsumption?

• Subsumption modifies inputs and outputs of other
  layers -- requires understanding of internals
• Instead, comm is higher level more explicit
• However, Gat calls this the fundamental tenant
  of subsumption
• Is it?