cs685-sensor-models - Sensors for Mobile Robots...

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1 SA-1 Probabilistic Robotics Probabilistic Sensor Models Beam-based Scan-based Landmarks 2 Sensors for Mobile Robots • Contact sensors: Bumpers • Internal sensors Accelerometers (spring-mounted masses) Gyroscopes (spinning mass, laser light) Compasses, inclinometers (earth magnetic field, gravity) • Proximity sensors Sonar (time of flight) Radar (phase and frequency) Laser range-finders (triangulation, tof, phase) Infrared (intensity) • Visual sensors: Cameras • Satellite-based sensors : GPS 3 Proximity Sensors The central task is to determine P(z|x) , i.e., the probability of a measurement z given that the robot is at position x . Question : Where do the probabilities come from? Approach : Let’s try to explain a measurement. 4 Beam-based Sensor Model Scan z consists of K measurements. Individual measurements are independent given the robot position.
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2 5 Beam-based Sensor Model 6 Typical Measurement Errors of an Range Measurements 1. Beams reflected by obstacles 2. Beams reflected by persons / caused by crosstalk 3. Random measurements 4. Maximum range measurements
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This note was uploaded on 04/07/2010 for the course CS 685 taught by Professor Luke,s during the Fall '08 term at George Mason.

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cs685-sensor-models - Sensors for Mobile Robots...

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