Robots are often used in industry to handle flexible objects, such as frames, leather goods, thin plates and rubber tubes. Most of the earlier studies dealt with handling of rigid objects and only a few have focused on the collaborative manipulators handling flexible objects. Therefore in this book two rigid robot manipulators collaboratively moving the flexible object in the desired trajectory and also suppressing the vibration of the object are considered for the study. The complete system of dynamic equations is obtained with the help of derived kinematic relations and dynamic equations of manipulators as well as the flexible object. Then, by employing singular perturbation technique slow and fast subsystems are identified. In order to handle parameter uncertainties, robust control algorithms are suggested. As a further improvement of control law for the slow subsystem, two control algorithms are suggested. The first one focused on the avoidance of velocity signal measurement which is useful to eliminate the need of velocity sensors and the second controller aims at avoiding the complex regressor in the control law. Stability analysis and simulation results are also presented.

Robots are often used in industry to handle flexible objects, such as frames, beams, thin plates, rubber tubes, leather goods and composite materials. Moving long flexible objects in a desired path and also precise positioning and orienting the objects need a collaborative action between two robot arms. Most of the earlier studies have dealt with manipulation of rigid objects and only a few have focused on the collaborative manipulators handling flexible objects. Such studies on handling of flexible objects generally used finite element method or assumed mode method for deriving the dynamic model of the flexible objects. These approximation methods require more number of sensors to feedback the vibration measurements or require an observer. Unlike in the earlier studies, this thesis concerns with development of a dynamic model of the flexible object in partial differential equation (PDE) form and design of a robust control strategy for collaborative manipulation of the flexible objects by two rigid robot arms. Two planar rigid manipulators each with three links and revolute joints handling a flexible object is considered during the model development. Kinematic and dynamic equations of the flexible object are derived without using any approximation techniques. The resulting dynamic equation of the flexible object together with the manipulator dynamic equations form the combined dynamic model of the system. The developed complete system of dynamic equations is described by the PDE's having rigid as well as flexible parameters coupled together. Such a coupled system must be controlled without using any form of approximation techniques and this is accomplished using the singular perturbation approach. By utilizing this technique, slow and fast subsystems are identified in two different time scales and controller is designed for each subsystem. The key issue in developing a control algorithm is that, it should be robust against uncertain parameters of the manipulators and the flexible object and it should also achieve the exponential convergence. Hence, for the slow subsystem, sliding mode control algorithm is developed and for the fast subsystem, a simple feedback control algorithm is designed. In general, usage of singular perturbation technique necessitates exponential stability of the slow and fast subsystems, which is evaluated by satisfying the Tikhnov's theorem. Hence, the exponential stability analysis for both the subsystems is performed. Simulation results are presented to validate the composite control scheme. As a further consideration in the improvement of control law for the slow subsystem, two modified control algorithms are suggested. The first one focused on the avoidance of velocity signal measurement which is useful to eliminate the need of velocity sensors and the second controller aims at avoiding the complex regressor in the control law. The capability of those controllers is illustrated through simulation studies. The extension of earlier analysis has been carried out by developing the complete system of dynamic equations in joint space.

Since the manipulation tasks for robotic systems become more and more complicated, multi-robot cooperation has been attracting much attention recently. Furthermore, under the trend of human-robot co-existence, collision-free motion control is now also desired on multi-robot groups. This dissertation aims to design a novel distributed optimal control framework to deal with multi-robot cooperative manipulation of rigid objects in dynamic environments. Besides object transportation, the control scheme also tackles obstacle avoidance, joint-space performance optimisation and internal force suppression. The proposed control framework has a two-layer structure, with a distributed optimisation algorithm in the kinematic layer for generating proper joint configuration references, followed by a robot motion controller in the dynamic control layer to fulfil the reference. An indirect and a direct distributed optimisation method are developed for the kinematic layer, both of which are computationally and communicationally efficient. In the dynamic control layer, impedance control is employed for safe physical interaction. As another highlight, abundant experiments carried out on a multi-arm test bench have demonstrated the effectiveness of the presented control schemes under various environmental and task settings. The recorded computation time shows the applicability of the control framework in practice.

Overviews manufacturing systems from the ground up, following the same concept as in the first edition. Delves into the fundamental building blocks of manufacturing systems: manufacturing processes and equipment. Discusses all topics from the viewpoint of four fundamental manufacturing attributes: cost, rate, flexibility and quality.

This book presents the proceedings of the third Vehicle and Automotive Engineering conference, reflecting the outcomes of theoretical and practical studies and outlining future development trends in a broad field of automotive research. The conference’s main themes included design, manufacturing, economic and educational topics.

Nowadays, our expectations of robots have been significantly increases. The robot, which was initially only doing simple jobs, is now expected to be smarter and more dynamic. People want a robot that resembles a human (humanoid) has and has emotional intelligence that can perform action-reaction interactions. This book consists of two sections. The first section focuses on emotional intelligence, while the second section discusses the control of robotics. The contents of the book reveal the outcomes of research conducted by scholars in robotics fields to accommodate needs of society and industry.