Artificial Coordinating Field Based Motion Planning of Mobile Robots

Abstract

Motion planning of mobile robots in uncertain dynamic environments has been a hot topic in robotic literature. It requires a mobile robot to decide its motion behaviour on line using limited and noised information of the local environment from sensors. There are many methods having been proposed to deal with this problem (Salichs and Moreno 2000, Jing 2005). Noticeably, artificial potential field (APF) based methods have gained increasingly popularity among researchers due to its high safety, simplicity and elegance (Khatib 1986, Rimon and Koditschek 1991, Kant and Zucher 1988, Rimon and Koditschek 1992, Koren and Borenstein 1991, Guldner and Utkin 1995, Ge and Cui 2000, Prassler 1999, Noborio et al 1995, Krogh 1984, Satoh 1993, Louste and Liegeois 2000, Wong and Spetsakis 2000, Singh et al 1997, Tsourveloudis et al 2001, Masoud and Masoud 2000). However, when the involved environment is totally or partially unknown or even dynamically changing, local minima are usually encountered, where the robot is trapped and cannot move on. There may also be unnecessary oscillations on the planned trajectory between multiple obstacles (Koren and Borenstein 1991). These inhibit the practical applications of this methodology to a certain extent. To overcome these problems, there are already some methods having been proposed in literature. For example, Krogh (1984) proposed a generalized potential field, in which the strength of repulsion is directly proportional to the speed of approach and inversely proportional to the minimum avoidance time. Satoh (1993) proposed Laplace potential field, which requires the potential field to be harmonic, and satisfy the Laplace equation. In Louste and Liegeois (2000), the authors used viscous fluid field instead of conventional APF to achieve near optimal path planning. Moreover, electric-like fields (Wong and Spetsakis 2000), magnetic field (Singh et al 1997), electrostatic potential field (Tsourveloudis et al 2001) were all proposed for the navigation and motion planning problems. But all these methods either require some global environment information or only deal with navigation problems in static environments, and only a few take into consideration of the actual dynamic constraints of the mobile robot such as saturations of velocity and acceleration. Moreover, few of the existing potential fields can guarantee the safety and reachability of the mobile robot with consideration of the actual dynamic constraints in uncertain dynamic environments.