Title :
Kalman Filter based position estimation using "optical mouse movement sensor" and differential drive robot model
Author :
Csaba, Gyorgy ; Vamossy, Zoltan
Author_Institution :
John von Neumann Fac. of Inf., Obuda Univ., Budapest, Hungary
Abstract :
This article describes the creation of a mathematical model for the kinematics, dynamics and electronics of a two-wheel-steered robot. As a result, it is possible to use a previously created, potential field-based and fuzzy navigation-based robot control system ([1], [2], [3], [4]) with two-wheel-driven robots as well. Using the results presented in this article the current location and the driven path can be estimated more accurately. This can be achieved by using the Kalman Filter with the wheel encoder data and using Optical Flow-based movement measurement devices that are similar to the ones known from the optical mouse peripherals. The established equations define the bases for controlling and navigating robots in indoor environments (flat surface, no sliding). According to these, they reflect the kinematics of the ground unit, the mathematical model of the electronic motor, and also the models of the sensors installed on the robot (odometer and optical mouse movement sensor).
Keywords :
Kalman filters; distance measurement; fuzzy control; indoor environment; mobile robots; navigation; optical sensors; position control; robot dynamics; robot kinematics; sensor fusion; Kalman filter based position estimation; differential drive robot model; driven path estimation; electronic motor; flat surface; fuzzy navigation-based robot control system; ground unit kinematics; indoor environment; location estimation; mathematical model; odometer; optical flow-based movement measurement device; optical mouse movement sensor; optical mouse peripheral; potential field-based robot control system; robot dynamics; robot electronics; robot kinematics; robot navigation; sensor model; two-wheel-driven robot; two-wheel-steered robot; wheel encoder data; Mathematical model; Mobile robots; Optical variables measurement; Robot kinematics; Robot sensing systems; Wheels;
Conference_Titel :
Applied Machine Intelligence and Informatics (SAMI), 2014 IEEE 12th International Symposium on
Conference_Location :
Herl´any
Print_ISBN :
978-1-4799-3441-6
DOI :
10.1109/SAMI.2014.6822402