using infrared proximity sensors for close 2d localization ... presentations/using-infra… ·...
TRANSCRIPT
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Using infrared proximity sensors for close 2D localization and object size recognition
Richard Berglind
Neonode
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• Overview of sensor types
• IR proximity sensors and their drawbacks
• Principles of a distributed sensor
• Robot implementation
Outline
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Sensor types
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• Camera
• LIDAR
• Time of flight
• Ultrasound
• IR proximity
Sensor types
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• 2D image of the surrounding environment
• Stereo vision or structured light to help determine distance and object shape
• Image processing required
• Camera FOV limits the minimum sensor to object distance
Camera
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• Scans a series of light pulses to generate a ”point cloud” of the surrounding environment
• Distance based on return time of pulses
• Suitable for long range applications
• Expensive
LIDAR
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• Phase shift method
• 2D-chip generates 3D image
• Requires calibration
• Temperature sensitive
• Accuracy ~1 cm
• Improve accuracy at the expense of frame rate
• Difficult to measure very short distances
Time of flight
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• Speed of sound ~340 m/s
• Round trip 50 cm distance ~3ms
• Sensor array: tradeoff between frame rate and resolution
Ultrasound
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IR proximity
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Basic proximity components
Emitter (LED/laser)
Receiver (PD)
Light blocker
Field of view
Emitted light
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Diffuse object scatters light in all directions
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A fraction of the scattered light is detected
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Detector signal decreases with distance
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What about the reflectivity (bright/dark objects)?
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Object shape recognition
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Object shape recognition – striped objects
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Distributed sensor
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• Alternating emitters and receivers
• Collimating optics
• Receiver field of view at an angle toward the emitters
• Each sequentially scanned emitter is used in combination with several receivers
• Object position is determined based on relative signal levels and geometry
• Independent of material reflectivity
Distributed sensor concept
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Emitter (laser/LED)
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Receiver field of view
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Multiple emitters
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Emitter-receiver maxima for one receiver
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Emitter-receiver maxima for multiple receivers
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Two viewing directions for every receiver
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Full set of emitter-receiver maxima
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Short distance
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Long distance
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Lateral resolution – signal ratio between emitters
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Distance resolution – signal ratio between receivers
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Accuracy: < 5 mm
Resolution: 0.1 mm
Maximum scanning frequency: ~900 Hz
Typical power consumption: 45-110 mW
Specifications
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• Each emitter generates a distance value
• Distance values for multiple emitters can be translated into an object shape with the same resolution as the distance between the emitters (7.2 mm)
Shape recognition
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Shape recognition – different shapes
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Shape recognition – striped objects
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Robot implementation
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• Multidisciplinary team of students from the University of Twente, Netherlands
• Autonomous robot soccer team with eight robot players
• Computer controlled during games
• Cameras above the field track general positions of ball and robots
• Rapid and precise 2D-localization of the ball relative the robot is required for good ball handling
Roboteam Twente
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Roboteam Twente – soccer playing robot
Courtesy of Roboteam Twente
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Roboteam Twente – soccer playing robot
Courtesy of Roboteam Twente
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Roboteam Twente – robot response
Courtesy of Roboteam Twente
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• Ordinary IR proximity sensor generates ambiguous and possibly erroneous data
• Distributed sensor overcomes this by using a geometric approach
• Fast, accurate 2D-localization and shape recognition
• Well suited for robot applications
Summary
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