Robotics Introduction Robot Hardware Robotic Perception Planning to Move Dynamics and Control Robotic Software Applications.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

Introduction

Robots are equipped with effectors.

Effectors Actuators

Assert a force on Communicates a the environment command to an effector

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.

Types of Robots

3. Hybrid (mobile with manipulators)Examples: humanoid robot(physical design mimics human torso)Made by Honda Corp. in Japan.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

Robot Hardware

Sensors:a. Passive sensors.

True observers such as cameras.

b. Active sensorsSend energy into the environment,like sonars.

Sensors

Examples of sensors:

• Tactile sensors (whiskers, bump panels)• Global Positioning System• Imaging sensors• Odometry (distance travelled)

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.

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

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.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

Robotic Perception

Can be illustrated using a Bayesian Belief Network.

It can be defined as a temporal inferencefrom sequences of actions and measurements.

Other Robotic Tasks

1. Localization2. Mapping3. Perception of

a. Temperatureb. Odorsc. Acoustic signals

Quantities can be estimated probabilistically.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

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).

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).

Configuration Space

The space can be decomposed into two subspaces:

a. Free space. Space of attainable configurations.b. Occupied Space. Space of unattainable configurations.

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.

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).

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.

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.

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.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

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.

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

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

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.

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

Robotic Software

• Three layer architecture• reactive layer ( low-level control)• executive layer (which reactive behavior to invoke?)• deliberate layer (planning)

Robotics

• Introduction• Robot Hardware• Robotic Perception• Planning to Move• Dynamics and Control• Robotic Software• Applications

Applications

• Industry and AgricultureAssembly linesHarvest, MineExcavate earth

• TransportationAutonomous helicoptersAutomatic wheelchairsTransport food in hospitals

Applications

• Hazardous environmentsCleaning up nuclear wasteCollapse of World Trade CenterTransport bombs

• ExplorationSurface of MarsUnder the seaMilitary activities

• Health Care (surgery)• Personal Services

Applications

•Health Care Surgery

• Personal Services• Entertainment

Dog-like robots• Human Augmentation

A Video

https://www.youtube.com/watch?v=6feEE716UEk