Path Following with an Optimal Forward Velocity for a Mobile Robot

Abstract

Abstract:In this paper, we present a novel solution for a path following problem in partially-known static environments. Given linearized error dynamic equations, model predictive control (MPC) is employed to produce a sequence of angular velocities. Since the forward velocity of the robot has to be adapted to environmental constraints and robot dynamics while the robot is following a path, we propose an optimal solution to generate the velocity profile. Furthermore, we integrate an obstacle-avoidance behavior using local sensor information with a path-following behavior based on global knowledge. To achieve this, we introduce new waypoints in order to move the robot away from obstacles while the robot still keeps following the desired path. Extensive simulations and experiments with a physical unicycle mobile robot have been conducted to illustrate the effectiveness of our path following control framework.

State of the Art in Predictive Control of Wheeled Mobile Robots

“…It was noticed that, in the works concerning predictive control, differentially driven robots and three-wheeled omnidirectional robots are predominant. The works [6,7,12,22,24,28,31,32,43] concern two-wheeled robots, and work [6] concerns inverted pendulum robot. In turn, works [2,5,10,20,21,29,38] describe three-wheeled omnidirectional robots, whereas [1,4,18,35], three-wheeled robots with two fixed driven wheels and castor.…”

“…In the reviewed literature concerning predictive control of WMRs, in the example works [2,5,11,17,18,21,22,28,44,46] authors mainly use the second approach, because it is more promising for more effective solution of the problem.…”

“…In [1] example of approach to stability study based on Lyapunov function is given. Other works on this problem include [3,22,31,42]. One may notice that despite its significance, the problem of control system stability is rarely considered in the works concerning predictive control of wheeled mobile robots.…”

Controle NMPC para o Seguimento de Caminhos Visuais com Velocidade de Navegação Variável

“…Mesmo para o rastreamento caminhos geométricos préespecificados no plano do mundo, cujas coordenadas de referência são dadas a priori, originalmente, não são permitidas variações na velocidade de navegação (Micaelli e Samson (1994)). Nesse caso, existem soluções pontuais, como Kanjanawanishkul et al (2010) através de uma ca-mada adicional de controleótimo e Burke (2012) com uma proposta para compensação do deslizamento. Soluções específicas para variação de velocidade de controladres para seguimento de caminhos visuais também são encontradas em Delfín et al (2014) para a navegação de robôs humanóides e (Seon et al, 2015) através de um modelo do tipo monociclo para implementar um seguimento caminho visual independente da velocidade.…”

A snake-based scheme for path planning and control with constraints by distributed visual sensors

“…49 One advantage of model predictive control is its ability to handle constraints. 50 For an autonomous vehicle, predictive capability is essential and therefore model-based predictive control was applied to achieve optimal path tracking subject to vehicle constraints, [51][52][53] where the approach of model predictive control is applied to a linearized robot model for the optimization of a quadratic objective function. For an uncertain and dynamic environment, predictive capability is more important for a mobile robot.…”