introduction to ai robotics chapter 7. the hybrid deliberative/reactive paradigm 2012. 11. 14
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Introduction to AI Robotics Chapter 7. The Hybrid Deliberative/Reactive Paradigm 2012. 11. 14. Hyeokjae Kwon. Objectives. Describe the hybrid paradigm in terms of 1 ) SPA and 2 ) sensing organization. - PowerPoint PPT PresentationTRANSCRIPT
Introduction to AI Robotics Chapter 7. The Hybrid Deliberative/Reactive Paradigm
2012. 11. 14
Hyeokjae Kwon
Objectives• Describe the hybrid paradigm in terms of 1) SPA and
2) sensing organization.• Given a list of responsibilities, be able to say whether it be-
longs in the deliberative layer or in the reactive layer.• List the five basic components of a Hybrid architecture: se-
quencer agent, resource manager, cartographer, mission planner, performance monitoring and problem solving agent.
• Be able to describe the difference between managerial, state hierarchy, and model-oriented styles of Hybrid archi-tectures.
• Be able to describe the use of state to define behaviors and deliberative responsibilities in state hierarchy styles of Hy-brid architectures.
Basic Important concept• Paradigm
– Paradigm is both a way of looking at the world and an implied set of tools for solving problems.
• Sense, Plan, Act.– Commonly accepted robotic primitives.– Robotics have to go through these three, or at
least two process to complete a mission.• Local Processing and Global World Model
– Local: sensor data used in specific for each func-tion.
– Global: all sensor data is processed to single model.
Hierarchical Paradigm• What are the two main features?
– Robot operates in a top-down fashion.– All sensor data tends to be gathered to
one global world model. A single repre-sentation that planner can use to rout the action.
SENSE PLAN ACT
Reactive Paradigm• What are the two main features?
– Throw out planning all together.– The inputs to an act are the direct out-
put of sensors.
SENSE ACT
Hybrid Paradigm• Features of Hybrid Deliberative/Reactive
Paradigm– It is reactive planning, Planning to subtask is done
at one step.– Deliberative planning take a long time comparing
to the time of reactive execution.– Sensor data go directly to each behavior but also
available to the planner for construction of task-oriented global world model.
– Model-based Architecture focuses on the creation and maintenance of a global world model.
Hybrid Paradigm• The basic models of Hybrid Paradigm
– Sequencer: generates a set of behaviors for subtasks.
– Resource manger: allocates resources to behavior
– Cartographer: for creating, storing, maintaining map or spatial information.
– Mission Planner: Interact with human and cre-ate a plan to achieve a goal
– Performance Monitoring: monitor the process of the executing, It’s self-awareness.
Hybrid Paradigm• Organization : Plan, Sense-Act
Motivation of Hybrids• Cohesion (object oriented programming)
– Reactivity:• Short time horizon (Present)• No global knowledge• Work with sensors and actuators
– Deliberation:• Long time horizon (Past, Future)• Global knowledge• Work with symbols
• Multi-tasking– Deliberative functions execute in parallel with
reactive functions.
Sensing OrganizationThe Map (World Model)
– Can have its own sensors– Can “eavesdrop” on other sensors– Can act as “virtual” sensor
World Map/ Knowledge
Rep
Behavior
Behavior
Behavior
Sensor 3
Sensor 1Sensor
2
Virtual sensor
Behavior control only
Feed-back
Planning only
Eaves-drop
Connotations of Global• “Global” isn’t always truly global in
Hybrids.• Behavioral Management
– Planning which behaviors to use requires knowledge about current and future world state
• Performance monitoring– Detecting task progress and sensor confliction require
knowledge about the robot hardware and the overall goals.
Architecture Styles• Managerial (division of responsibility as
in business)– AuRA : Autonomous Robot Architecture– SFX : Sensor Fusion Effects
• State Hierarchies (strictly by time scope)– 3T : 3-Tiered
• Model-Oriented (Model serve as virtual sensors)– Saphira – TCA : Task Control Architecture
Styles of hybrid architec-tures
● Managerial styles
● State hierarchies styles
● Model-oriented styles
Managerial Architectures• Description -- top agents – high level planning
↓ subordinate agents – refine plan, gather resources ↓ lowest level agents
▲ AuRA Architectures
▲ SFX Architectures
Autonomous Robot Architecture (AuRA)
• It consists of five subsystems -- planner : responsible for mission and task plan-ning
-- cartographer : all map making, reading functions
-- motor : motor schema
-- sensor
-- homeostatic control : modify the relationship between behaviors by changing the gain as a function of robot or other constraints
AuRA Architectural LayoutCartographer
Sequencer
MissionPlanner
Behavioral manager(mgr+schemas)
PerformanceMonitoring
Emergent behavior
reac
tive
deli b
erat
ive
The table below summarizes AuRA in term of the common components and style of emergent behavior
AuRA SummarySequencer Agent Navigator, PilotResource Manager Motor Schema ManagerCartographer CartographerMission Planner Mission Planner
Performance Monitoring Agent Pilot, Navigator, Mission Planner
Emergent Behavior
Vector summation, spreading activation of behaviors, homeostatic control
Sensor Fusion Effects (SFX)• description – It is an extension to
AuRA. The extension was to add modules to specify how sensing and handling sensor failure.
Sensor Fusion Effects (SFX)• Deliberative layers
-- Mission planner : acts as a CEO giving a directions
-- effector
-- Task
-- Sensor All of three of above determine the best alloca-tion of effect, sensing resource and perceptual schema. -- Cartographer : map making, path planning
SFX (Sensor Fusion Effects)
Behaviors(using direct
perception, fusion)
SenseSenseSenseSenseMuscleMuscleMuscleActuators
Deliberative Layer Managers
SenseSenseSenseSensor
SenseSenseSenseReceptiveField
Choice of behaviors, resourceallocation, motivation, context
Focus of attention,recalibration
SensorWhiteboard
BehavioralWhiteboard
Del
iber
ativ
e La
yer
Rea c
tive
L ay e
r Parameters to behaviors,sensor failures, task progress
actions
SuperiorColliculus-likefunctions
CerebralCortex-likefunctions
Cartographer(model/map
making)Recognitionperception
Sensor Fusion Effects (SFX)• Reactive layers
All these layers reflect to - strategic behaviors and tactical behaviors
Tactical behavior serves as filter on strategic commands to ensure to robot acts in a safe manner in as close accordance with the strate-gic intent as possible
The interaction of strategic and tactical be-haviors is still considered emergent behavior.
Tactical Behaviorssensors strategic behaviors tactical behaviors actuators
follow-path speed-controlcamera drivemotor
avoidsonarsteermotor
center-cameracamerapanmotor
inclino-meter
slope
clutter
obstacleshow much vehicle turns
direction to path safe direction
safe velocity
swivel camera
strategicvelocity
The table below summarizes SFX in term of the common components and style of emergent behavior
SFX Summary
Sequencer Agent Task Manager
Resource Manager Sensing and Task Manager
Cartographer Cartographer
Mission Planner Mission PlannerPerformance Monitoring
Agent Performance Monitor, Habitat Monitor
Emergent Behavior Strategic behaviors grouped into abstract
behaviors or scripts, then filtered by
tactical behaviors
State-hierarchy Architectures• 3 – tiered (3T)
3 – tiered (3T)• Structure
-- planner : setting goal and strategic plans -- sequencer : select a set of primitive behaviors develop a task network -- skill manager : in this layer the skills have associated events to verify explicitly that an action has had to correct effect
3T Architecture
The table below summarizes 3T in term of the common components and style of emergent behavior
3T
Sequencer Agent Sequencer
Resource Manager Sequencer (Agenda)
Cartographer Planner
Mission Planner PlannerPerformance Monitoring
Agent Planner
Emergent Behavior Behaviors grouped into skills,
skills grouped into task
network
Model-oriented Architec-tures
• Two of best-known model-oriented architecture▲Saphira Architecture▲Task Control Architecture
Saphira Architecture -- PRS-Lite it is capable of taking natural language voice com-mands from humans and then operationalizing that into navigation tasks and perceptual recognition routines.
-- virtual sensor
-- navigation tasks manage the behaviors
-- LPS (Local Perceptual Space) determine the planning and execution improve the quality of the robot’s overall behavior
Saphira Architecture
The table below summarizes Saphira in term of the common components and style
of emergent behavior
Saphira
Sequencer Agent Topological planner, Navigation
Tasks
Resource Manager PRS-Lite
Cartographer LPS
Mission Planner PRS-LitePerformance Monitoring
Agent PRS-Lite
Emergent Behavior Behaviors fused with fuzzy logic
Task Control Architecture (TCA)
-- Task Scheduling (Mission Planner) determine the goal and order of execution
-- Path Planning (Cartographer)
-- Navigation (Sequencer) to determine what the robot should be looking for, where it is, where it has been.
-- Obstacle Avoidance To factor in not only obstacle but how to respond with a smooth trajectory for the robot’s current velocity.
Task Control Architecture (TCA)
The table below summarizes TCA in term of the common components and style of emer-gent behavior
TCASequencer Agent Navigation Layer
Resource Manager Navigation Layer
Cartographer Path-Planning Layer
Mission Planner Task Scheduling LayerPerformance
Monitoring Agent Navigation, Path-Planning,
Task-Scheduling
Emergent Behavior Filtering
Thank you!