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Transcript of Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control...
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Introduction
Robots are equipped with effectors.
Effectors Actuators
Assert a force on Communicates a the environment command to an effector
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Types of Robots
1. Manipulators Anchored to the workplace. Common industrial robots.
2. Mobile Robots Move using wheels, legs, etc. Examples: delivering food in hospitals, autonomous navigation, surveillance, etc.
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Types of Robots
3. Hybrid (mobile with manipulators)Examples: humanoid robot(physical design mimics human torso)Made by Honda Corp. in Japan.
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Robot Hardware
Sensors:a. Passive sensors.
True observers such as cameras.
b. Active sensorsSend energy into the environment,like sonars.
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Sensors
Examples of sensors:
• Tactile sensors (whiskers, bump panels)• Global Positioning System• Imaging sensors• Odometry (distance travelled)
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Effectors
Characterized by the degrees of freedom DF.
DF counts one for each independent directionof movement.
6 degrees of freedom are required to place an object at a particular orientation.
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Other Types of Effectors
Unlike wheels, legs can handle tough terrains,but they are slow on flat surfaces.Devices vary from one leg to dozens of legs.
Robots can be• dynamically stable• dynamically unstable
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Sources of Power
• The electric motor is the most popular source
• But you may also see:• Pneumatic actuation using compressed gas.• Hydraulic actuation using pressurized fluids.
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Robotic Perception
Can be illustrated using a Bayesian Belief Network.
It can be defined as a temporal inferencefrom sequences of actions and measurements.
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Other Robotic Tasks
1. Localization2. Mapping3. Perception of
a. Temperatureb. Odorsc. Acoustic signals
Quantities can be estimated probabilistically.
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Planning to Move
Types of motion:
a. Point-to-Point. Deliver robot to target location.
b. Compliant motion. Move while in contact to an obstacle (robot pushing a box).
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Configuration Space
Working Space: Spatial coordinates.Problem: not all coordinates are attainable
Configuration Space: Represent robot joints.With two joints we need two angles(e.g., for shoulder and elbow).
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Configuration Space
The space can be decomposed into two subspaces:
a. Free space. Space of attainable configurations.b. Occupied Space. Space of unattainable configurations.
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Methods to Move
Cell Decomposition.
Decompose the free space into a number of contiguous regions, called cells.
The problem is a discrete graph search problem.
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Methods to Move
Cell Decomposition.
Disadvantages:
a. Limited to low-dimensional configurations.b. Cells may be “mixed”. (solution: make cells more granular).c. Path may get too close to obstacles. (solution: use a potential field).
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Potential Field
A function defined over state space.Value grows with distance to closest obstacle.
Tradeoff:
Minimize path length to goal while staying away from obstacles.
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Skeletonization
Reduce free space to a one-dimensionalrepresentation. Lower representation is called a skeleton.
Example is a Voronoi graph. (points equidistant to two or more obstacles). Steps:-) Follow Voronoi graph until close to target-) Leave graph and move to target.
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Probabilistic Roadmap
Create random graph by creating a largenumber of configurations. Discard those that do not fall into free space.
Then join any two nodes by an arc if it is easyto reach one node from the other.
Method is incomplete but scales better to highdimensional configurations.
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Dynamics and Control
Keeping a robot on track is not easy.
Use a controller to keep the robot on track.
Controllers that provide a force in negativeproportion to the observed error are knownas P controllers.
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Dynamics and Control
Let y(t) be the reference path.The control generated by the controllerhas the form:
a(t) = K ( y(t) – x(t) )
K: gain parameter
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Dynamics and Control
To achieve stability we use a PD controllerP – proportionalD – derivative
a(t) = K1 ( y(t) – x(t) ) + K2 d ( y(t) - x(t) ) / dt
K1: gain parameterK2: differential component
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Reactive Control
In some cases reflex-agents are more appropriate.
When a leg’s forward motion is blocked, Simply retract it, lift it higher, And try again.
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Robotic Software
• Three layer architecture• reactive layer ( low-level control)• executive layer (which reactive behavior to invoke?)• deliberate layer (planning)
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Robotics
• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications
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Applications
• Industry and AgricultureAssembly linesHarvest, MineExcavate earth
• TransportationAutonomous helicoptersAutomatic wheelchairsTransport food in hospitals
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Applications
• Hazardous environmentsCleaning up nuclear wasteCollapse of World Trade CenterTransport bombs
• ExplorationSurface of MarsUnder the seaMilitary activities
• Health Care (surgery)• Personal Services
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Applications
•Health Care Surgery
• Personal Services• Entertainment
Dog-like robots• Human Augmentation
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A Video
https://www.youtube.com/watch?v=6feEE716UEk