Modeling the positioning accuracy of sensor-based robots
Markku Järviluoma, Tapio A. Heikkila
Abstract
Markku Järviluoma, Tapio A. Heikkila
Abstract
This paper describes a method for expressing and manipulating position and orientation uncertainty in sensor-based robotics. The goal is to formulate a computational framework where the effects of accumulating uncertainties, originating from internal and external sensors, are shown as uncertainties in tool frame positions and orientations. The described method is based on using covariance matrices of position and orientation parameters. The used orientation parameters are xyz Euler angles. There are three different forms of spatial uncertainty and uncertainty manipulation involves transformations between these forms. These transformations are done by using linearization around nominal relations. Paper presents the basic formulas for these transformations and also three calculation examples.
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This paper describes a method for expressing and manipulating position and orientation uncertainty in sensor-based robotics. The goal is to formulate a computational framework where the effects of accumulating uncertainties, originating from internal and external sensors, are shown as uncertainties in tool frame positions and orientations. The described method is based on using covariance matrices of position and orientation parameters. The used orientation parameters are xyz Euler angles. There are three different forms of spatial uncertainty and uncertainty manipulation involves transformations between these forms. These transformations are done by using linearization around nominal relations. Paper presents the basic formulas for these transformations and also three calculation examples.
Key concepts: Orientation (vector space), Position (finance), Euler angles, Linearization, Frame (networking), Covariance, Robotics, Computer science