A continuous dynamic modeling approach for an omnidirectional mobile robot

Abstract

MY wheel-II is one of switch omnidirectional wheel mechanisms. The omnidirectional mobile robot based on MY wheels-II is a switched non-linear system (i.e. discontinuous system). The aim of this paper is to propose a continuous modeling approach which can be employed to derive a continuous model from any given discontinuous robot dynamic model. This approach results in a continuous non-linear parameter varying (NLPV) model, and offers one solution for model-based control design. Firstly, our previously proposed average dynamic modeling approach is analyzed. We find that this modeling approach is effective only for a specific class of robot configurations. To overcome this problem, we first derive the switching conditions of MY wheel-II. Based on derived switching conditions, we then propose a simple continuous NLPV modeling approach. The new approach replaces the real discontinuous contact radius in the discontinuous dynamic model with an adaptive continuous curve. An illustrative example of the adaptive continuous curve design is provided. Both simulation and experimental results verify the effectiveness of the proposed NLPV modeling approach against the average modeling approach.

Passivity-based tracking control of an omnidirectional mobile robot using only one geometrical parameter

“…It can be seen from (9) and (14) that the only required model parameter in implementation of the designed control system is the contact radius L 0 , which is the geometrical information of robot. Compared with traditional model-based control design, such as RAC in [2], the tedious dynamic modeling and parameter identification process can be avoided.…”

“…As a result, the proposed control design may be an attractive option from an implementation point of view. In addition, it can be seen in the observer (9) and controller (14) that only the position feedback signal is needed without measuring the robot velocity. Remark 2.…”

“…OMRs are typical nonlinear, time-varying, multi-input-multioutput systems, subject to various external disturbances (i.g., uncertain payload, friction forces). In the literature, the dynamic modeling and control of OMRs have been studied by many researchers in recent two decades [2][3][4][5][6][7][8][9][10][11]. In [2], a feedback linearization approach, resolved acceleration control (RAC), was applied to an OMR with three lateral orthogonal-wheel assemblies, in which the control performance depends on the accuracy of the dynamic model.…”

“…In [8], a switching quasi-linear-parameter-varying controller using LMI-based techniques was proposed for a four-wheeled OMR. Considering wheel switching, a continuous dynamic modeling and control approach of an OMR were discussed in [9] and [10], respectively. An observer was used to estimate the complicated dynamics, unmodeled dynamics and input-output cross-couplings in [10].…”

Improved 3D sparse maps for high-performance SFM with low-cost omnidirectional robots

“…Research on mobile navigation in complex environments has been significantly boosted with the manoeuvrability of holonomic robots [1,2]. A holonomic robot platform has as many actuators as degrees of freedom.…”