Adaptive Coordinated Cooperative Control of Multi-Mobile Manipulators

VICTOR ANDALUZ; LEICA PAULO; FLAVIO ROBERTI; TOIBERO, J. M.; RICARDO CARELLI

Frontiers in Advanced Control Systems

InTech

Año: 2012; p. 163 - 190

A coordinated group of robots can execute certain tasks, e.g. surveillance of large areas (Hougen et al., 2000), search and rescue (Jennings et al., 1997), and large objects-transportation (Stouten and De Graaf, 2004), more efficiently than a single specialized robot (Cao et al., 1997). Other tasks are simply not accomplishable by a single mobile robot, demanding a group of coordinated robots to perform it, like the problem of sensors and actuators positioning (Bicchi et al., 2008), and the entrapment/escorting mission (Antonelli et al., 2008). In such context, the term formation control arises, which can be defined as the problem of controlling the relative postures of the robots of a platoon that moves as a single structure (Consolini et al., 2007). Mobile manipulator is nowadays a widespread term that refers to robots built by a robotic arm mounted on a mobile platform. This kind of system, which is usually characterized by a high degree of redundancy, combines the manipulability of a fixed-base manipulator with the mobility of a wheeled platform. Such systems allow the most usual missions of robotic systems which requiere both locomotion and manipulation abilities. Coordinated control of multiple mobile manipulators have attracted the attention of many researchers (Khatib et al., 1996; Fujii et al., 2007; Tanner et al., 2003; Yasuhisa et al., 2003). The interest in such systems stems from the capability for carrying out complex and dexterous tasks which cannot be simply made using a single robot. Moreover, multiple small mobile manipulators are also more appropriate for realizing several tasks in the human environments than a large and heavy mobile manipulator from a safety point of view. Main coordination schemes for multiple mobile manipulators that can be found in the literature are: 1)Leader–follower control for mobile manipulator, where one or a group of mobile manipulators plays the role of a leader, which track a preplanned trajectory, and the rest of the mobile manipulators form the follower group which moves in conjunction with the leader mobile manipulators (Fujii et al., 2007; Hirata et al., 2004; Thomas et al., 2002). In Xin and Yangmin, 2006, a leader-follower type formation control is designed for a group of mobile manipulators. To overcome parameter uncertainty in the model of the robot, a decentralized control law is applied to individual robots, in which an adaptive NN is used to model robot dynamics online. 2)Hybrid position–force control by decentralized/centralized scheme, where the position of the object is controlled in a certain direction of the workspace and the internal force of the object is controlled in a small range of the origin (Khatib et al., 1996; Tanner et al., 2003; Yamamoto et al., 2004). In Zhijun et al., 2008, robust adaptive controllers of multiple mobile manipulators carrying a common object in a cooperative manner have been investigated with unknown inertia parameters and disturbances. At first, a concise dynamics consisting of the dynamics of mobile manipulators and the geometrical constraints between the end-effectors and the object is developed for coordinated multiple mobile manipulators. In Zhijun et al., 2009 coupled dynamics are presented for two cooperating mobile manipulators manipulating an object with relative motion in the presence of uncertainties and external disturbances. Centralized robust adaptive controllers are introduced to guarantee the motion and force trajectories of the constrained object. A simulation study to the decentralized dynamic control for a robot collective consisting of nonholonomic wheeled mobile manipulators is performed in Hao and Venkat, 2008, by tracking the trajectories of the load, where two reference signals are used for each robot, one for the mobile platform and another for end-effector of the manipulating arm. To reduce performance degradation, on-line parameter adaptation is relevant in applications where the mobile manipulator dynamic parameters may vary, such as load transportation. It is also useful when the knowledge of the dynamic parameters is limited. As an example, the trajectory tracking task can be severely affected by the change imposed to the robot dynamics when it is carrying an object, as shown in (Martins et al., 2008). Hence, some formation control architectures already proposed in the literature have considered the dynamics of the mobile robots (Zhijun et al., 2008; Zhijun et al., 2009). In this Chapter, it is proposed a novel method for centralized-decentralized coordinated cooperative control of multiple wheeled mobile manipulators. Also, it is worth noting that, differently to the work in Hao and Venkat, 2008, we use a single reference for the end-effector of the robot mobile manipulator. Although centralized control approaches present intrinsic problems, like the difficulty to sustain the communication between the robots and the limited scalability, they have technical advantages when applied to control a group of robots with defined geometric formations. Therefore, there still exists significant interest in their use. As an example, in Antonelli et al., 2008, a centralized multi-robot system is proposed for an entrapment/escorting mission, where the escorted agent is kept in the centroid of a polygon of n sides, surrounded by n robots positioned in the vertices of the polygon. Another task for which it is important to keep a formation during navigation is large-objects transportation, since the load has a fixed geometric form. Another recent work dealing with centralized formation control is Mas et al., 2008, where a control approach based on a virtual structure, called Cluster Space Control, is presented. There, the positioning control is carried out considering the centroid of a geometric structure corresponding to a three-robot formation. In this Chapter, the proposed strategy conceptualizes the mobile manipulators system (with ) as a single group, and the desired motions are specified as a function of cluster attributes, such as position, orientation, and geometry. These attributes guide the selection of a set of independent system state variables suitable for specification, control, and monitoring. The control is based on a virtual 3-dimensional structure, where the position control (or tracking control) is carried out considering the centroid of the upper side of a geometric structure (shaped as a prism) corresponding to a three-mobile manipulators formation. It is worth noting that in control problem formulating first it is considered three mobile manipulators robots, and then is generalized to mobile manipulators robots. The proposed multi-layer control scheme is mainly divided in five modules: 1) the upper module is responsible for planning the trajectory to be followed by the team of mobile manipulators; 2) the next module controls the formation, whose shape is determined by the distance and angle between the end-effector of a mobile manipulator and the two other ones; 3) another module is responsible to generate the control signals to the end-effectors of the mobile manipulators, through the inverse kinematics of each robot. As a mobile manipulator is usually a redundant system, this redundancy can be used for the achievement of additional performances. In this layer two secondary objectives are considered: the avoidance of obstacles by the mobile platforms and the singular configuration prevention through the control of the system’s manipulability; introduced by Yoshikawa (1985). 4) The adaptive dynamic compensation module compensates the dynamics of each mobile manipulator to reduce the velocity tracking error. It is worth noting that this controller has been designed based on a dynamic model having reference velocities as input signals. Also, it uses a robust updating law, which makes the dynamic compensation system robust to parameter variations and guarantees that no parameter drift will occur; 5) finally, the robots module represents the mobile manipulators. It is worth noting that we propose a methodology to avoid obstacles in the trajectory of any mobile manipulator based on the concept of mechanical impedance of the interaction robots-environment, without deforming the virtual structure and maintaining its desired trajectory. It is considered that the obstacle is placed at a maximum height that it does not interfere with the workspace, so that the arm of the mobile manipulators can follow the desired trajectory even when the platform is avoiding the obstacle.