1. 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

2. 2 Overview Two difficult situations of using wheelchair Form 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

3. 3 Hardware Design Mechanical Part Rear wheels : two differentially driven Front wheels : two passive castor Maximum speed : 6 km/h (Powered by 12 V battery)

4. 4 Hardware Design Central Processing Industrial PC(Pentium 166 MHz) + QNX Sensors Dead-reckoning system : wheel encoders + optical fiber gyroscope 3 x 8 Ultrasound transducers and microcontrollers Short-range sensing : two infrared scanners 2-D laser range-finder

5. 5 Hardware Design (Cont’d)

6. 6 Control Architecture WAN : Hierarchical Control Architecture Tactical Level Strategic Level Basic Control Level

7. 7 Basic Control Level Desired velocity vector Actual value computed by dead-reckoning Desired velocity

8. 8 Tactical Level (Overview) The core of WAN Module Motion Detection Motion Tracking & Obstacle Velocity Estimation Computation of the Evasive Maneuvers

9. 9 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

10. 10 Strategic Level Main task Navigating 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

11. 11 Motion Detection and Tracking A sequence of single observation Investigating where these observations differ from each other Discrepancy  potential change Occupancy Grid Representation A 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

12. 12 Time Stamp Map Modification of occupancy grid representation Map only cells observed as occupied Cell coinciding with the range measurement All other cells  left untouched Range image  200 x 200 time stamp map Takes 1.5 msec on a Pentium 166 MHz

13. 13 Motion Detection Algorithm Based on a simple heuristic Cell is occupied by a stationary object if corresponding cells in TSM t and TSM t-1 carry time stamps. By a moving object if corresponding cells in TSM t carry a time stamp different from TSM t-1 or no no time stamp at all. TSM t : Time Stamp Map at time t

14. 14 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 Euclidean distance The ensembles describes the same object  if the distance to the nearest neighbor is smaller than a certain threshold. Threshold For stationary object : 30cm For moving object : 1 m

15. 15 Motion Planning For simplicity Model the wheelchair and the obstacles as circles.  Planar problem with no rotations obstacle Wheelchair

16. 16 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 V A outside VO

17. 17 Velocity Obstacle (cont’d) Collision Cone v.s. Velocity Obstacle Avoiding multiple obstacles : Prioritization among Vos Velocity Obstacle Collision Cone

18. 18 Velocity Obstacle (cont’d) Consideration of wheelchair dynamics Some heuristics for making trajectory Reachable Velocity Reachable Avoidance Velocity Velocity Obstacle Toward GoalMaximum VelocityStructure

19. 19 Experiments in Real Situations Roaming in a Railway Station Hall size : 20 x 40 m 2 Several tens of people Survived about 18 hours Hannover Fair ’98 Survived more than 36 hours