New Directions in Network Intrusion Detection

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					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

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

• We’ll talk about
– The Old School: Sense-Plan-Act – The Brooks School: Subsumption – The Modern School: Three-Layer

a typical robot
Processor Sensors

Actuators Sensors

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

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 just want to be loved

I am about to fall over

A goal’s priority naturally will change based on context

slicing the problem: spa
Task Execution
Motor Control

Perception

Modeling

Sensors

Planning

Actuators

All goals are known at each stage, and affect the computation

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

new architecture: subsumption
• 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.

slicing the problem: subsumption
reason about object behavior
plan changes to the world

Sensors

monitor changes build maps explore wander avoid objects

Actuators

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

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 selfcentered 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)

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

...and failures?
• Herbert didn’t 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

three-layer architectures
• “Response” to subsumption, simultaneously and independently developed by >3 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?

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
– Can’t we all just get along?

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.)

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?


				
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