EE887 Special Topics in Robotics

Paper Review

Initial Results in the Development

of a Guidance System Guidance System for a Powered Wheelchairfor a Powered Wheelchair2000. 6. 7.

BSCLLee Hyong Euk

General Idea of this paper

The autonomous navigation and the control of wheelchair

What are the issues in the wheelchair application? User Interface Obstacle avoidance Battery usage Seating Comport User demographics …

The navigation(guidance) of the wheelchair,Particularly the estimation and control of the system

Focus :

Requirement for Wheelchair Application

1. System must be more accurate2. System must be robust and repeatable3. Smooth ride to ensure user comport4. System should be simple and inexpensive5. Remember that the passenger is a human being

Requirement for Wheelchair Application

1. System must be more accurate2. System must be robust and repeatable3. Smooth ride to ensure user comport4. System should be simple and inexpensive5. Remember that the passenger is a human being

This requirements need ‘exact position estimation’

Experimental Wheelchair System

<Fig1. Experimental Wheelchair System>

<Fig2. Wheelchair Schematic>

512 by 480 pixel CCDBlack and white

1000 count-per revolutionOptical encoders

The camera view is not blocked by the user’s lower extremities.Everest & Jennings Powered Wheelchair

26 inches

Approach (1)

Odometry information(wheel rotation)External vision-based observation of surrounding envrionment

Combining and ApplyingExtended Kalman Filter algorithm

Optimal estimate of the wheelchair’s pose

Observation or measurement noise are modeled by Gaussian Distributed white process A set of diff. Equation which relate wheel motion to the position and orientation of the wh

eel chair are numerically integrated to produce the so-called “dead-reckoned”

Approach (2)

Automatic Guidance of the wheelchair “Teach-repeat” Procedure

The role of two video camera Detect the cues in the surroundings

Approach (2)

Automatic Guidance of the wheelchair “Teach-repeat” Procedure

The role of two video camera Detect the cues in the surroundings

: Reference hints for pos. estimation(ex. Desk, wall, or any fixed one in the workspace)

16 cues were used for this system (some objects in the experimental workspace)

‘cue’ is a priori information

Approach (3)

<Fig3. Wheelchair system guidance Flowchart>

Experiments

Test environment : home, office, classroom, laboratory, … Load : 200-lb human passenger and other equipments(PC, …) Floor surface : smooth poured concrete, tile, various carpet type

Room layout with nominal path

Ref. Path was taught in the Mechanical Systems and Robotics Lab.At the University of Notredam

Experiment Results (1)

Tracking Ref. Path Result

Total Time : 175s Avr. Speed : 0.5 ft/s 16 cues

Experiment Results (2)

Tracking Ref. Path Result with obstacle avoidance

Manual Control for obstacle avoidance

Experiment Results (3)

Speed Control : error between actual and estimated position

< Nominal Speed : 0.5ft/s > < Lower Speed : 0.3ft/s >

Avr. X error (in)

Avr. Y error (in)

Max. X error (in)

Max. Y error (in)

Nominal speed 1.006 1.167 2.884 2.393

Low speed 0.175 0.146 0.369 0.393

For 10 consecutive run case

Discussion

1. The extended Kalman filter accurately estimate the system’s pose(position & orientation)

2. The limitation of evaluating accuracy depend on the position of the ‘cue’s. a total of four cues were available for the last 8 ft of the path.

3. The obstacle avoidance strategy must be developed

4. User interface and other considerable factor is remained jobs.