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Smart Wheelchairs. Friday, 4/8/2011 Professor Wyatt Newman. Outline. What/Why Smart Wheelchairs? Incremental Modules Reflexive collision avoidance Localization, trajectory generation, steering and smart buildings Speech-driven wheelchair control Natural language interfaces .
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Smart Wheelchairs Friday, 4/8/2011 Professor Wyatt Newman
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) sensors reflexes/local mapping Wheelchair command
“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) volitiveexpressions 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: SPEECH Rec. & Prod. Visual display ! ? Parsing & Inter- pretation Sensor signal Motor action Obstacle avoidance Local Ontology Incl. sites and known objects
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