Sensors and Methods for Mobile Robot Positioning

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Systems-at-a-Glance Tables Landmark Positioning Name Computer Onboard Features used Accuracy - Accuracy - Sampling Features Effective Reference Components position [mm] o orientation [ ] Rate [Hz] Range, Notes Iconic position Locomotion em- Cyclone laser range In general, has a Max. 36 mm Max. 1.8º Iconic method works Assume small dis- [Gonzalez et al., estimator ulator, all-wheel scanner, resolution large number of mean 19.9 mm mean 0.73º directly on the raw placement between 1992] drive and all- =10 cm short line segments sensed data, minimizing sensed data and Carnegie Mellon wheel steer, range = 50m the discrepancy between model University Sun Sparc 1 1000 readings per it and the model Two parts: sensor rev. to map data correspondence & error minimization Environment rep- Geometrical rela- A graph where the The recognition [Taylor, 1991] resentation from tionships between nodes represent the ob- problem can be for- Yale University image data observed features served features and mulated as a graph rather than their edges represent the rela- matching problem absolute position tionships between features Localization via Sonars Local map: multi- Using datasets from Local grid Positioning by classify- Matching: K-near- [Courtney and Jain, classification of Lateral motion vi- sensor 100×100 10 rooms and hall- maps ing the map descriptions est neighbor and 1994] multi-sensor maps sion grid maps, cell ways, estimate a 94% Feature-level to recognize the minimum Texas Instruments, Infrared proximity 20×20 cm recognition rate for sensor fusion workspace region that a Mahalanobis dis- Inc. sensor rooms, and 98% for by extracting given map represents tance hallways spatial descriptions from these maps 232
Systems-at-a-Glance Tables Other Navigation Techniques Name Computer Onboard Maps and Accuracy - Accuracy - Sampling Features Effective Reference Components Features position [mm] orientation Rate [Hz] Range, o [ ] Nnotes Guide path sensor 0.01-0.1 m 100-1000 or analog External, local, or 0.01-0.2 m [Parish and Grab- (magnetic, optical, waypoint indication, ble, 1993] inductive, etc.) $100-$5K Omnitech Robotics, Inc. Odor trails for nav- Applicator for lay- Unlimited [Russell et al., igation ing volatile chemi- 1994] cals on the floor; Monash University olfactory sensor Thermal path fol- Quartz halogen 0.833 No need to remove Unlimited [Kleeman and Ruslowing bulb and markers after use sell, 1993] pyroelectric sensor Monash University 233
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7KH8QLYHUVLW\RI0LFKLJDQ Where am I?
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Acknowledgments This research was s
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2.4.2.2 Watson Gyrocompass ........
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6.4 Summary .......................
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INTRODUCTION Leonard and Durrant-Wh
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Part I Sensors for Mobile Robot Pos
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14 Part I Sensors for Mobile Robot
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CHAPTER 2 HEADING SENSORS Heading s
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6 42 Part I Sensors for Mobile Robo
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CHAPTER 5 ODOMETRY AND OTHER DEAD-R
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R e t r o r e f l e c t i v e m a r
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Page 222 and 223: Systems-at-a-Glance Tables Odometry
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Page 236 and 237: REFERENCES 1. Abidi, M. and Chandra
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Page 262 and 263: 262 Index AC ..............47, 59,
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