Obstacle avoidance

ugliestmysticAI and Robotics

Nov 14, 2013 (3 years and 11 months ago)

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Friday, 4/8/2011


Professor Wyatt Newman

Smart Wheelchairs

Outline


What/Why Smart Wheelchairs?


Incremental Modules


Reflexive collision avoidance


Localization, trajectory generation, steering and
smart buildings


Speech
-
driven wheelchair control


Natural language interfaces

Architecture


Natural language/
speech processing

localization/motion
control (or joystick)


reflexes/local mapping

Wheelchair command

sensors

“Otto”
instrumented
wheelchair



*Kinect


*Hokuyo


*“Neato”


*ultrasound

Sensing the world


All mobile vehicles should avoid collision.


“Ranger” sensors


Actively emit energy to detect obstacles


Cameras


Passively absorb light and can use machine vision
techniques to estimate obstacle positions.

Rangers


Simple rangers


Can be sonar or infrared.


Limited information arises from wide “cone” emitted by
sensor.



Laser Scanners


Lidars (LI Detection And Ranging)


Much better information.


Many radial points of data.


Velodyne


Three dimensional lidar.


Very expensive.



Laser Scanners




Neato

sensor:


Low
-
cost sensor


1
-
deg range values


Not yet available as


separate unit


Cameras


Monocular cameras cannot return depth information.


Stereo cameras do return depth information.


This requires two sensors and has computational and
calibration overhead.


Hybrid sensor: Swiss Ranger


Uses infrared time of flight calculations with a monocular
camera to produce a 3D map.


Kinect sensor:


Low
-
cost, mass
-
produced camera for computer gaming


Uses structured light to infer 3
-
D

Autonomous Mode


Localization


Relative frame


Global frame


Navigation


Goal planning


Path planning


Path following/Steering

Localization


Local frame sensors


Odometry


Gyros


Accelerometers


Fusion with Kalman Filter


Drifty and unreliable for long term position
estimation

Localization


Global frame


SLAM (Simultaneous Localization & Mapping)


AMCL (Adaptive Monte Carlo Localization)

Navigation


Rviz (robot’s perception)



video

Smart Building


Coordination & Cooperation


Smart devices work together to improve quality of
life for users


Multi
-
robot path planning and congestion control


Robots invoke services within buildings



video


Vocal Joystick


A hands free control system for a wheelchair will
provide restored independence


Quadriplegics, ALS, MS, Cognitive Disorders, Stroke


Assistive Technology


High Level of Abandonment


Comfort


Difficult interface


Doesn’t properly fit the problem


Hard
to make small adjustments


Alternative Wheelchair
Control


Voiced


Path
Selection vs. Goal
Selection (“Go to
”)



“Natural”
language
commands
(Left, Right)


Non
-
Voiced


Humming
controller


Mouth
-
Controlled


“sip and puff”


tongue

Alternative Wheelchair
Control


Head Joystick


Eye movement (“Gaze”)


Chin Control


EMG

Why not voice?


Voice is the most natural way to interface
with a
wheelchair. Why have
we not seen
voice activated wheelchairs in the market?


Recognition
problems


Over simplified


Difficulty in precision control without collision avoidance


Difficult HMI


Hard to make small adjustments

Speech
-
driven Wheelchair
Control


A
naturalistic “vocal” joystick for a wheelchair (or any
other mobile vehicle).


Prosodic features will be extracted from the user when
giving a command
.


Pitch, Stress, and Intensity


Modeled
and learned (through training simulations
)


Uses
a Small corpus


Users wont have to manage many commands.


With added prosodic features could provide a more natural
means and solve the small changes in velocity, a problem
described earlier.


video

A linguistic interface



Longer
-
term research in natural human
interfaces



There are three ways to think and speak about
space in order to travel through it.


(1) MOTION driving, (2) voyage DRIVING, and (3) goal
driven speech control of motion:
(1)

>(2)

>(3)


We control each others’ movements, when it is relevant,
by (1) motor
commands
, (2)
indications of paths
, and (3)
volitive

expressions of goals. So:


Speaking to a taxi driver,
(3)
the mention of a goal is
normally enough to achieve proper transportation.


Speaking to a private driver as his navigator, we would
instead give
(2)
indications for the trajectory by referring
to perceived landmarks.


Speaking to a blindfolded person pushing your wheelchair,
we would finally just use

(1)
commands corresponding to
simply using a joystick in a videogame.

Interface Architecture:



Local Ontology

Incl. sites and known objects

SPEECH

Rec. &

Prod.

Visual

display

Sensor

signal

Parsing

& Inter
-

pretation

Motor

action

?

!

Obstacle avoidance

Future Work


Wheelchair as personal assistant


Safety monitoring


Health monitoring


Assistive functions


Wheelchair users focus group input


User trials


Add
-
on modules


Automated seat pressure redistribution


Medication reminders/monitoring


BP and weight monitoring


Distress sensing/response

Summary/Q&A


Reflexive collision avoidance

near
-
term product?


Localization, trajectory generation and steering


Verbal joystick w/ prosody


a priori
maps vs. teaching/map
-
making;


smart buildings/smart products


Natural language processing and human interfaces

longer term