Sliding Mode Control for Visual Servoing of Mobile Robots using a Generic Camera

Abstract

At present, vision sensors represent a very good option for the control of robots since they provide at a low cost a lot of information from the environment. The feasibility of using a vision system as the only source of feedback information has been shown by many approaches (Chaumette & Hutchinson (2006), Chaumette & Hutchinson (2007)). Particularly, incorporating machine vision for the control of mobile robots can improve their navigation capabilities (DeSouza & Kak (2002)). The approach of closing the control loop through a vision system is called visual servoing (VS). The schemes in this control approach can be classified according to the nature of the feedback information. Image data can be used directly in the control loop (image-based schemes IBVS), for instance (Abdelkader et al. (2005), Benhimane & Malis (2006)), or can be used to compute an estimate of pose parameters (position-based schemes: PBVS) as in (Das et al. (2001), Fontanelli et al. (2009)). Hybrid schemes combining these both approaches have been performed as well (Malis et al. (1999), Fang et al. (2005)). Most of the current efforts of the research on visual servoing focus on applications of monocular vision. This chapter presents an IBVS approach to drive a wheeled mobile robot equipped with a monocular camera onboard to a desired pose (position and orientation). The desired pose is specified by a target image previously acquired, i.e., the teach-by-showing strategy. In this context, a good way to relate the current and the target view is through a geometric constraint: epipolar geometry or the homography model. A geometric constraint is imposed on images in which there exist correspondences between features (Hartley & Zisserman (2000)). The information provided by a geometric constraint can be used directly as measurement for output feedback control. Comparing this two-view geometric constraints, the epipolar geometry is a more general approach because it is not constrained to planar objects or planar scenes. Currently, there also exist approaches that use three views (Becerra et al. (2010)). This chapter focuses on exploiting the epipolar geometry (EG) in an IBVS approach. This constraint has been applied in some works (Basri et al. (1998), Rives (2000), Mariottini et al. (2007), Lopez-Nicolas et al. (2008)). These works deal with the teach-by-showing problem, in which the target pose must be reached using only image data provided from the current and target images. In (Basri et al. (1998)) and (Rives (2000)) are reported visual servoing schemes based on epipolar geometry for manipulators. In the field of mobile robots, an epipolar-based VS approach that takes into account the nonholonomic nature of the robots is introduced in Sliding Mode Control for Visual Servoing of Mobile Robots using a Generic Camera 12