A Robotic Wheelchair for Crowded Public Environments

2001. 6. 7.Choi Jung-Yi

EE887 Special Topics in Robotics Paper Review

E. Prassler, J. Scholz, and P. Fiorini, “A robotic wheelchair for crowded public environments,” IEEE Robotics & Automation Magazine, vol. 7, no. 1, pp. 38-45, 2001

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Overview

Two difficult situations of using wheelchairForm conversations with the user community

Navigation in NARROW & CLUTTERED environments

WIDE & CROWDED areas

MAid (Mobility Aid for Elderly and Disabled People) Combines

Narrow Area Navigation (NAN) Behavior Semiautonomous Navigation Mode

Wide Area Navigation (WAN) Behavior Autonomous Navigation Mode

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Hardware Design

Mechanical PartRear wheels : two differentially drivenFront wheels : two passive castorMaximum speed : 6 km/h (Powered by 12 V battery)

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Hardware Design

Central ProcessingIndustrial PC(Pentium 166 MHz) + QNX

SensorsDead-reckoning system : wheel encoders + optical fiber gyroscope3 x 8 Ultrasound transducers and microcontrollersShort-range sensing : two infrared scanners2-D laser range-finder

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Hardware Design (Cont’d)

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Control Architecture

WAN : Hierarchical Control Architecture

TacticalLevel

StrategicLevel

Basic ControlLevel

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Basic Control Level

Desired velocity vector

Actual value computed by dead-reckoning

Desired velocity

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Tactical Level (Overview)

The core of WAN Module

Motion Detection

Motion Tracking & Obstacle Velocity Estimation

Computation of the Evasive Maneuvers

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Tactical Level (Overview) cont’d

Past trajectory and velocity

Sonar system Monitoring the surrounding environment

Detect the environment objects

Identify stationary / moving object

Estimate the speed and direction of the object

Laser range finder

Determine if MAid is moving on s collision course with objects

Compute the avoidance maneuver

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Strategic Level

Main taskNavigating in crowded area

Reaching a specific goal

Without any intermediate goal

Selection the nest motion goal by the user

Strategic level will be expended by including a path planner capable of adding the computation of subgoal sequences

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Motion Detection and Tracking

A sequence of single observation

Investigating where these observations differ from each other

Discrepancy potential change

Occupancy Grid RepresentationA projection of the range data on a 2-D rectangular grid

Grid element a small region of the real world

Updating every cell time consuming process

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Time Stamp Map

Modification of occupancy grid representation

Map only cells observed as occupiedCell coinciding with the range measurement

All other cells left untouched

Range image 200 x 200 time stamp mapTakes 1.5 msec on a Pentium 166 MHz

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Motion Detection Algorithm

Based on a simple heuristic

Cell is occupied by a stationary object if corresponding cells in TSMt and TSMt-1 carry time stamps.

By a moving object if corresponding cells in TSMt carry a time stamp different from TSMt-1 or no no time stamp at all.

TSMt : Time Stamp Map at time t

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Motion History

Objects are represented by cell ensembles in the sensor map.Identifying the object in a sequence of maps

Correspondence between objects using a nearest-neighbor criterion based on a Eu

clidean distanceThe ensembles describes the same object

if the distance to the nearest neighbor is smaller than a certain threshold.Threshold

For stationary object : 30cmFor moving object : 1 m

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Motion Planning

For simplicityModel the wheelchair and the obstacles as circles.

Planar problem with no rotations

obstacle

Wheelchair

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Velocity Obstacle

VO of A with respect to B

Identifying the set of velocities of A causing a collision with the obstacle B at some time

To avoid collision : selecting the tip of VA outside VO

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Velocity Obstacle (cont’d)

Collision Cone v.s. Velocity Obstacle

Avoiding multiple obstacles :Prioritization among Vos

Bmi VOVO 1

VelocityObstacle

CollisionCone

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Velocity Obstacle (cont’d)

Consideration of wheelchair dynamics

Some heuristics for making trajectory

Reachable Velocity

Reachable Avoidance VelocityVelocity Obstacle

Toward Goal Maximum Velocity Structure

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Experiments in Real Situations

Roaming in a Railway StationHall size : 20 x 40 m2

Several tens of people

Survived about 18 hours

Hannover Fair ’98Survived more than 36 hours