An application of Lyapunov stability analysis to improve the performance of NARMAX models

Otar Akanyeti*, Iñaki Rañó, Ulrich Nehmzow, S. A. Billings

*Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

11 Dyfyniadau(SciVal)


Previously we presented a novel approach to program a robot controller based on system identification and robot training techniques. The proposed method works in two stages: first, the programmer demonstrates the desired behaviour to the robot by driving it manually in the target environment. During this run, the sensory perception and the desired velocity commands of the robot are logged. Having thus obtained training data we model the relationship between sensory readings and the motor commands of the robot using ARMAX/NARMAX models and system identification techniques. These produce linear or non-linear polynomials which can be formally analysed, as well as used in place of "traditional robot" control code. In this paper we focus our attention on how the mathematical analysis of NARMAX models can be used to understand the robot's control actions, to formulate hypotheses and to improve the robot's behaviour. One main objective behind this approach is to avoid trial-and-error refinement of robot code. Instead, we seek to obtain a reliable design process, where program design decisions are based on the mathematical analysis of the model describing how the robot interacts with its environment to achieve the desired behaviour. We demonstrate this procedure through the analysis of a particular task in mobile robotics: door traversal.

Iaith wreiddiolSaesneg
Tudalennau (o-i)229-238
Nifer y tudalennau10
CyfnodolynRobotics and Autonomous Systems
Rhif cyhoeddi3
Dyddiad ar-lein cynnar19 Tach 2009
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 31 Maw 2010
Cyhoeddwyd yn allanolIe

Ôl bys

Gweld gwybodaeth am bynciau ymchwil 'An application of Lyapunov stability analysis to improve the performance of NARMAX models'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.

Dyfynnu hyn