1. Robotics From the book :
Robin R. Murphy, “Introduction to AI Robotics”, The MIT Press

2. What Are Robots? The word “robot” An Intelligent Robot
Rossum’s Universal Robots
January 25, 1921
First performance of Karel Capek’s play
Derived from the Czech word “robota” which means menial laborer
An Intelligent Robot
A mechanical creature which can function autonomously

3. Robotic Paradigms
Hierarchical
Reactive
Hybrid deliberative/reactive

4. What are Robotic Paradigms?
A philosophy or set of assumptions and/or techniques which characterize an approach to a class of problems
Applying the right paradigm makes problem solving easier
Three paradigms for organizing intelligence in robots
Hierarchical paradigm
Reactive paradigm
Hybrid deliberative/reactive paradigm

5. Robotic Paradigms The paradigms can be described in two ways
By the relationship between the three commonly accepted primitives
By the way sensory data is processed and distributed through the system.
ROBOT PRIMITIVES
INPUT
OUTPUT
SENSE
Sensor data
Sensed information
PLAN
Information
(sensed and/or cognitive)
Directives
ACT
Sensed information or directives
Actuator commands

6. Hierarchical Paradigm
PLAN
SENSE
ACT
SENSE
PLAN
ACT
The oldest paradigm ( )
Top-down fashioned operation
Heavy on planning
Control people hated because it isn’t “close the loop”
AI people hated because monolithic
Users hated because very slow

7. Reactive Paradigm SENSE-ACT couplings are “behaviors”
Behaviors are independent, run in parallel
Heavily used in
Users loved it because it worked
AI people loved it, but wanted to put PLAN back in
Control people hated it because couldn’t rigorously prove it worked

8. Hybrid deliberative/reactive paradigm
SENSE
ACT
PLAN
SENSE
ACT
PLAN
Control people hated it because AI, but are getting over it
AI people loved it
Users loved it

9. How AI related to a robot system?
Deliberative:
Upper level is mission generation & monitoring
But World Modeling & Monitoring is hard
Lower level is selection of behaviors to accomplish task (implementation) & local monitoring
SENSE
ACT
plan
World
model
monitoring
generating
selecting
implementing
Reactive (fly by wire, inner loop control):
Many concurrent stimulus-response behaviors, strung together with simple scripting
Action is generated by sensed or internal stimulus
No awareness, no monitoring
Models are of the vehicle, not the “larger” world

10. How AI related to a robot system?
SENSE
ACT
plan
World
model
monitoring
generating
selecting
implementing
PLAN
SENSE
ACT
Converting sensor data into information:
Promising results: ATR, single failure health monitoring
Open issues: creation of world models & situation awareness, monitoring & detection of new threats, exceptions, opportunities
Reasoning over information about goals:
Promising results: Navigation, payload planning, contingency replanning
Open issues: Multi-agent replanning, fault recovery & reconfiguration, reasoning over multiple failures
Skills and responses

11. New trends on the horizon
Shape-Shifting
Legged Platform
Humanoids

12. Shape Shifting Snake-like robots Tracked vehicles Robot bugs
Rescue site
Narrow passage
Tracked vehicles
Rough terrain
Robust to turnover
Robot bugs
Ecological approach
High mobility

13. Legged Locomotion Advantages Examples Major issues
Moving through rugged terrain
Low power consumption
Examples
Hexapod
One-, two-, four-legged
Major issues
Maintaining balance
Getting up / sitting down
Dynamically adapting the gaits to terrain

14. Close proximity with human
Aibo
The best known robot pet
Non-verbal communication with human
Kismet
Facial robot
Physically expressive interfaces
Minerva
Tour guide robot
Expressive face

15. Humanoids Famous humanoids ASIMO, HONDA AMI, KAIST HUBO, KAIST
ROBONAUT, NASA
COG, MIT