a robotic wheelchair for crowded public environments
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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 communityNavigation in
NARROW & CLUTTERED environmentsWIDE & 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 ModuleMotion DetectionMotion Tracking & Obstacle Velocity EstimationComputation 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 objectsIdentify stationary / moving object
Estimate the speed and direction of the object
Laser range finder
Determine if MAid is moving on s collision course with objectsCompute the avoidance maneuver
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Strategic Level
Main taskNavigating in crowded areaReaching a specific goalWithout any intermediate goal
Selection the nest motion goal by the userStrategic 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 observationInvestigating where these observations differ from each otherDiscrepancy potential change
Occupancy Grid RepresentationA projection of the range data on a 2-D rectangular gridGrid element a small region of the real worldUpdating every cell time consuming process
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Time Stamp Map
Modification of occupancy grid representationMap only cells observed as occupied
Cell coinciding with the range measurementAll other cells left untouchedRange image 200 x 200 time stamp map
Takes 1.5 msec on a Pentium 166 MHz
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Motion Detection AlgorithmBased on a simple heuristicCell 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 rotationsobstacle
Wheelchair
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Velocity ObstacleVO of A with respect to BIdentifying 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 dynamicsSome 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 peopleSurvived about 18 hours
Hannover Fair ’98Survived more than 36 hours
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