Utilizing reflection properties of surfaces to improve mobile robot localization

Abstract-- A main difficulty that arises in the context of probabilistic localization is the design of an appropriate observation model, i.e., determining the likelihood of a sensor measurement given the pose of the robot and a map of the environment. Many successful approaches to localization rely on data provided by range sensors, e.g., laser range scanners. When using such data one normally has to deal with erroneous maximum-range readings that occur due to poor-reflecting surfaces. In general, these readings cannot be distinguished from readings obtained when no obstacle is within the measurement range of the sensor. Therefore, existing localization techniques treat these readings alike in the observation model. In this paper, we present a novel approach that explicitly considers the reflection properties of surfaces and thus the expectation of valid range measurements. In addition to the expected range measurement, we compute the probability of reflectance for a beam given the rel...

• Type: Journal
• Year: 2009
• Where: ICRA
• Authors: Maren Bennewitz, Cyrill Stachniss, Sven Behnke, Wolfram Burgard
• Keywords: ICRA 2009, Laser Range Scanner, Measurement, Observation Model, Robotics