Dynamics and Control for Nonholonomic Mobile Modular Manipulators

The development of a robot requires that it be able to adopt as many configurations as possible using limited modules, so as to allow the construction of new types of robots without redesign and remanufacturing. Traditionally, modular manipulators are mounted on a fixed base whose mobility is constrained. However, with the development of industry and technology, such modular manipulators as mounted on fixed bases can not meet some practical requirements any more. An intelligent and autonomous mobile manipulator, which can fulfil some operations without human interference, has become an active research topic recently since it has many potential applications such as in modern factories for transporting materials, in dangerous fields for dismantling bombs or moving nuclear infected objects, in modern families for doing housework, as well as in the public places for city maintenance. In this chapter, a nonholonomic mobile platform is attached to the modular manipulator in order to increase workspace of the entire robot. Building up the dynamic model for a nonholonomic mobile modular manipulator is a challenging task due to the interactive motions between the modular manipulator and the mobile platform, as well as the nonholonomic constraints of the mobile platform. Also a trajectory following task becomes even more complex and difficult to achieve. Such conventional control strategies as computed-torque control require precise apriori knowledge of the dynamic parameters for the controlled system. However, in practical applications, it is almost impossible to obtain exact dynamic parameters for a mobile modular manipulator because of such uncertainties as complex nonlinear frictions, flexibilities of the joints and links, payload variations, and terrain irregularities. Robust control techniques provide a natural rejection to external disturbances, which are provided by a high-frequency commuted control action that constrains the error trajectories to stay on the sliding surface. Classical sliding mode control law adopts sign functions and the caused chattering may do harm to the robots. Adaptive control technique does not rely on precise apriori knowledge of dynamic parameters and it can suppress such errors as caused by parameter uncertainties by online adjusting dynamic parameters. Furthermore, adaptive control can counteract the negative influence of highfrequency switching caused by robust control because its action has naturally smooth time behaviour.