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Course Objectives
• Know what it takes to make a robust autonomous
robot work:
– Sense/Think/Act
• Understand the important, approaches, research issues
and challenges in autonomous robotics.
• Know how to program an autonomous robot.
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What Can Robots Be Used For?
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Manufacturing
3 Ds
– Dirty
– Dull
– Dangerous
Space
– Satellites, probes, planetary landers, rovers
Military
Agriculture
Construction
Entertainment
Consumer?
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History of Intelligent Robotics
• 1940s
– First remote manipulators for hazardous
substances
• 1950s
– Industrial manipulators: “reprogrammable and
multi-functional mechanism designed to move
materials, parts, tools…”
– Closed loop control
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History Continued
• 1955 – term “AI” coined
• 1960s manufacturing robots
– Automatic guided vehicles (AGVs)
– Precision, repeatability
– Emphasis on mechanical aspects
• 1970s
– Planetary landers
– Machine vision research expands
• 1980s
– Black factory
– First intelligent autonomous robots:
• Shakey, Stanford Cart, etc
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History Continued
• 1990s
– Symbolic AI/Robotics stalls
– Reactive/Behavior-based robotics emerges
• 2000s
– ?
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Intelligent Robot
• Mechanical creature which can function
autonomously
– Mechanical= built, constructed
– Creature= think of it as an entity with its own
motivation, decision making processes
– Function autonomously= can sense, act, maybe even
reason; doesn’t just do the same thing over and over
like automation
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“Intelligent” Robotics
• Basic robot primitives :
Sense/Think/Act
• Three paradigms (architectures):
- Hierarchical (Deliberative):
Sense ->Plan ->Act ;
- Reactive:
Sense -> Act;
- Hybrid (Deliberative/Reactive):
Plan -> Sense -> Act
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Ways of Controlling a Robot
• “RC-ing”
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you control the robot
you can view the robot and it’s relationship to the environment
ex. radio controlled cars, bomb robots
operator isn’t removed from scene, not very safe
• teleoperation
– you control the robot
– you can only view the environment through the robot’s eyes
– don’t have to figure out AI
• semi- or full autonomy
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you might control the robot sometimes
you can only view the environment through the robot’s eyes
ex. Sojouner with different modes
human doesn’t have to do everything
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Teleoperation
• Human controls robot remotely
– Hazardous materials
– Search and rescue
– Some planetary rovers
• Considerations
– Feedback (video, tactile, smell?)
– User interfaces (cognitive fatigue, nausea)
– Time/distance
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Components of a Telesystem
(after Uttal 89)
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• Local
– display
– Local control device
• Communication
• Remote
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sensor
mobility
effector
power
Remote
Local
Display
Communication
Sensor
Mobility
Control
Effector
Power
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Example
Remote
Local
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Typical Run
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Problems that You Saw
• no feedback, couldn’t really tell that the robot was stuck
but finally got free
– robot doesn’t have “proprioception” or internal sensing to tell
you what the flippers were doing. No crunching noises, no
pose widget to show the flippers
• no localization, mapping-> no idea how far traveled
• partial solution: better instrumentation (but can’t do dead
reckoning well)
– operator doesn’t have an external viewpoint to show itself
relative to the environment
• solution: two robots, one to spot the other
• communications dropout, even though ~3 meters away
• lighting conditions went from dark to very bright
– hard for computer vision or human to adjust
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DarkStar+7 seconds=DarkSpot
• 7 second communications lag (satellite relay)
• “interruption” lag on part of operator
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Predator:
~7:1 human to robot ration
Leo’s unofficial
Predator page
• 4 people to control it (52-56 weeks of training)
– one for flying
– two for instruments
– one for landing/takeoff
• plus maintenance, sensor processing and routing
• lack of self-awareness– in Kosovo, come along side in helicopter
and shoot down
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Teleop Problems
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cognitive fatigue
communications dropout
communications bandwidth
communications lag
too many people to run one robot
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Telesystems Best Suited For:
• the tasks are unstructured and not repetitive
• the task workspace cannot be engineered to permit the
use of industrial manipulators
• key portions of the task require dexterous manipulation,
especially hand-eye coordination, but not continuously
• key portions of the task require object recognition or
situational awareness
• the needs of the display technology do not exceed the
limitations of the communication link (bandwidth, time
delays)
• the availability of trained personnel is not an issue
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Teleop Solutions
• Telepresence
– improves human control, reduces simulator sickness and cognitive
fatigue by providing sensory feedback to the point that teleoperator
feels they are “present” in robot’s environment
• Semi-autonomous
– Supervisory Control
• human is involved, but routine or “safe” portions of the task are handled
autonomously by the robot
• Shared Control
– human initiates action, interacts with remote by adding perceptual inputs or
feedback, and interrupts execution as needed
• Traded Control
– human initiates action, does not interact
– Mixed Initiative (Guarded Control)
• robot doesn’t let the operator injure the robot (without override)
• “whoever figures it out first”
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Collaborative Teleoperation
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mpg: June 2, 2000 SRDR Miami Beach: view from Inuktun as it falls
Urban is stuck, Inuktun can’t help from
current perspective
1. Driven off 3rd floor
2. Hoisted to 2nd floor by tether
3. Has better view, changing
configuration & rocking extend view
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mpg: June 2, 2000 SRDR Miami Beach: view from Inuktun from hoisted position
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still: June 2, 2000 SRDR Miami Beach
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2000 AAAI Mobile Robot
• 2 robots helping each other reduced collision errors,
sped up time navigating confined space, righting
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Example:
Mixed-Initiative & Collab. Teleop
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9/2000 DARPA Tactical
Mobile Robots demonstration
Robot used an intelligent
assistant agent to look for signs
of snipers hiding in urban
rubble
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motion
skin color
difference in color
thermal (IR camera)
Human navigated mother robot
using viewpoint of 2nd robot
(not in picture)
Once deposited the human
moved the daughter robot, and
either saw a sniper or was
alerted by the agent
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AI provides the “other stuff”
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knowledge representation
understanding natural langugage
learning
planning and problem solving
inference
search
vision
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Summary
• Teleoperation arose as an intermediate solution to
autonomy, but it has a number of problems:cognitive
fatigue, high comms bandwidth, short delays, and
many:one human to robot ratios.
Telepresence tries to reduce cognitive fatigue through
enhanced immersive environments
Semi-autonomy tries to reduce fatigue, bandwidth by
delegating portions of the task to robot
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