Trends in Robotics Research

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Trends in Robotics Research

• Classical AI Robotics (mid-70s)
• Sense-Plan-Act
• Complex world model and reasoning

Indoor, wheeled, static blocks world

• Reactive Paradigm (mid-80s)
• No models the world is the model
• Simple sense-act functions
• Emergent behavior

Static legged motion, robot swarms, reactive
Complex environments, mapping and
localization, human-robot interactions

• Hybrid Architectures (90s)
• Models at higher levels, reactive at lower
  levels
• Mid-level executive to sequence actions

Challenging outdoor environments Air, water
vehicles Dynamic legged motion

• Probabilistic Methods (mid-90s)
• Uncertain sensing and acting
• Integration of models, sensing, acting

Again Thanks to Steffen Gutmann for many
slides
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Classic AI Robotics

• Shakey (1967) at SRI Rosen, Nilsson, Hart
• First AI Robot
• Foundational study reason about the world,
  e.g., block a doorway
• How do you represent the environment?
• How do you plan to change the environment?

• Set of predicates describing the world
• AT(Box1, (32, 11))ON(Box2, Box1)
• Rules among the predicates (predicate logic)
• Operators describing how actions affect the world
• gt STRIPS planner

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Sense-Plan-Act Paradigm

• Architecture

Sense
Plan
Act
STRIPS
Exec
ILUs
DB

• Exec was in charge
• ILUs were reactive
• Opportunistic use of plans
• Replanning

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Shakey69

• Stanford ResearchInstitute

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Stanford CART 73
Stanford AI Laboratory / CMU (Moravec)
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Classical Paradigm -Stanford Cart

1. Take nine images of the environment, identify
   interesting points in one image, and use other
   images to obtain depth estimates
2. Integrate information into global world model
3. Correlate images with previous image set to
   estimate robot motion
4. On basis of desired motion, estimated motion, and
   current estimate of environment, determine
   direction in which to move
5. Execute the motion

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Classical Paradigm as Horizontal/Functional
Decomposition
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Classical Paradigm as Horizontal/Functional
Decomposition
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Behavioral Paradigm

• Reaction to perceived inadequacies of the SPA
  paradigm
• Brooks, Arkin, Payton
• Radical change use a short Sense-Act Cycle
• Many different incarnations
• Subsumption (Brooks, Connell, )
• Potential Fields, Motor Schemas (Arkin, Gat)
• Rule-based (Saffiotti, Ruspini, Konolige)
• Circuits (Gat, Rosenschein and Kaelbling-Pack)
• Biological Inspiration
• No complex data structures
• No complex sensory processing

• Vertical vs. Horizontal Decomposition

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Reactive Paradigm as Vertical Decomposition
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Behavioral Paradigm Tenets
Swarm robots

• Robots are situated
• No abstract thinking
• Interpretation of robot state depends on
  environment
• Behavior-based programming, emergent behaviors
• No hierarchical controller
• Distributed, concurrent behaviors
• Behavior-specific sensing
• Quick and dirty (e.g., seagull chicks)

Genghis

• How do behaviors combine?

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Motor Schema
Direct mapping from the environment to a control
signal
goal-seeking behavior
obstacle-avoiding behavior
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Motor Schema
path taken by a robot controlled by the resulting
field
vector sum of the avoid and goal motor schemas
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Behavior Design

• Behavior design is more an art than a science
• In what situation does the behavior apply?
• What is the result of the behavior?
• Easy to program?
• Robustness?
• Scalability?
• Good behaviors produce smoothly varying control
  signals
• Control signals that oscillate or otherwise jump
  around lead to poor control performance
• Emergent behavior is difficult to predict

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Project 1 Wall Following

• Find a wall to travel along
• Use right-hand rule keep wall on the right
• Keep a short distance from the wall, going
  parallel to it
• NOTE must interpret LRF readings by finding
  wall features
• Follow along inside and outside bends
• Go through reasonable openings (gt 1m)
• Suggestions
• Use behaviors for different situations along
  wall, far from wall, at inside corner, etc.
• Debug them separately
• Invoke behaviors based on the situation
• Use heading control rather than separate wheel
  velocities

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Complex Control Architectures

• Task there are three robots to deliver six
  packages to four people.
• Question how much force should Robot 1 apply to
  its left wheel?
• state -gt a1, a2 ... an

..\..\..\writings\talks\videos\flakey
etc\flakey-sap.avi
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Final Project (Fall 2001)
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QRIOs Navigation Architecture

• Each module runs in own thread
• Message passingbetween modules
• Aperios/OPEN-Rreal-time system

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Environment Classification

• 6 different types
• Floor
• Stairs
• Border
• Tunnel
• Obstacle
• Unknown

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Configuration and Modularity
Only enabled actions are allowed when expanding a
node during path search
Motion behavior is selected based on the types of
cells on the path and on the path direction as
reported by the path planner.
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Experiments
narrow obstacles
Stairs (2 x 3cm)
Table (35 cm)
QRIO autonomously navigates on an obstacle course
(IJCAI-2005)
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Video