Publication

Estimating the Odometry Error of a Mobile Robot during Navigation

Roland Siegwart
2003
Conference Papers

Abstract

This paper addresses the problem of the odometry error estimation during the robot navigation. The robot is equipped with an external sensor (like laser range finder). Concerning the systematic error an augmented Kalman Filter is introduced. This filter estimates a vector state containing the robot configuration and the parameters characterizing the systematic component of the odometry error. It uses encoder readings as inputs and the readings from the external sensor as observations. The estimation of the non-systematic component is carried out through another Kalman Filter where the observations are obtained by two subsequent robot configurations provided by the previous augmented Kalman Filter. Both synchronous and differential drive systems are considered.

Official source

https://infoscience.epfl.ch/entities/publication/2c7095bd-6284-4811-9af0-112a3f1328cc

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Roland Siegwart
2003
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/2c7095bd-6284-4811-9af0-112a3f1328cc

About this result

Related concepts (32)

Kalman filter

For statistics and control theory, Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, who was one of the primary developers of its theory.

Robot navigation

Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localisation, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference. For any mobile device, the ability to navigate in its environment is important.

Mobile robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" (AMR - autonomous mobile robot) which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices.

Related publications (32)

Estimating the Odometry Error of a Mobile Robot during Navigation

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