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The ability of walking is related to various daily tasks, while the lack of mobility can decrease significantly the quality of life of people affected by diseases related to locomotion. The etiology of those diseases can be from distinct origins, such as neurological, genetic, cardiovascular, among others. As a result of the lack of mobility, affected people may have difficulties to perform basic tasks and this can bring problems in several stages of their lives, such as labor, and socialization and even psychological issues may appear. In order to try to help those people, researchers from all over the world try to improve or create treatments and devices which may help them. Some of those researches are about smart walkers, which are walkers that rely on electronics and control systems, besides the mechanical structure. Since those devices use sensors and actuators, they may improve the gait of those people who can use this kind of device, helping them in their physical rehabilitation process. Furthermore, smart walkers can help people who may not have enough force to use a conventional walker, but can rely on a smart walker, since it uses engines to help the orientation and propulsion. This kind of device can, therefore, help more people that conventional walkers and be an aid for physiotherapy sessions. This work shows an adaptation of a conventional walker into an robotic smart walker, by connecting the conventional walker to a robot.

In this work a mobile robot cooperation strategy based on computational vision is presented. Such strategy is applied to a mobile robot team formed by simple and cheap robots and a leader robot with more computational power. The leader has an omnidirectional visual system and uses color segmentation to obtain the pose of the followers. This visual information is used by a nonlinear stable controller that manages team formation. Simulations and tests were run and current results are encouraging.

Surveillance and transport of parts are important tasks associated with mobile robots actuating between cells in a flexible production system. or between different sections in an industrial plant. For transporting, depending on the dimensions of the parts, more than one robot is necessary and the part can be shared among several robots. This work presents a methodology for creating a structure containing mobile robots and a vision system, which is used for tasks of surveillance and transport of parts either between cells in a flexible production system or in an industrial plant.

In this paper, a time delay compensation control structure for a robot teleoperation system is presented. The structure design was made considering 1.9-seconds time delay in the communication between the remote and local stations. The objective is to control both the remote manipulator's position and force. Force and position signals are fedback to the local station so that the human operator feels in his/her hand the force associated with the task being executed at the remote site. Simulations are carried out considering the dynamic model of the hwnan operator in the control loop. In this sense, simulations show a good perfonnance of the proposed compensation control structure.

This work presents a control strategy applied to robot manipulators operating close to kinematic singularities. Considering the robot to be in contact with the environment, a PD controller is iInplelnented with inverse dynamics compensation to control the robot manipulator. In order to accomlTIodate the forces originated froln the interaction with the environment, the control systelTI includes an impedance loop that modifies the robot's references accordingly. In the vicinity of a singularity, the algorithm generates a fictitious force to which a second impedance function is applied. This causes a small deviation to the original robot trajectory to avoid the singularity region. The algoritlun is based on the minimwn singular value of the Jacobian matrix in order to generate the module and direction of the fictitious force. This strategy is applied to a teleoperation system without time delay

This paper presents the application of a combined control strategy grounded in a basic Model Predictive Control (MPC) structure, but using a Discrete Fuzzy Model (DFM) of the process in the state space domain. Two methods of optimization are tested. The first one is the traditional sequential method where the model is solved at each iteration of the optimization routine. The second is the simultaneous method, which integrate the solution of the model into the optimization problem, provided the fulfillment of some conditions in the DFM. A particular DFM that fulfill such conditions is presented. The advantages and disadvantages of the two methods are exposed in accordance with the results of simulation tests. Finally, some conclusions and future research topics are given

A methodology for obtaining the stnlcture and parallleters of a Takagi-Sugeno fuzzy model is proposed. The algorithm is divided into two steps: coarse tuning and fine tuning. In coarse tuning, the model structure identification is based on partial derivatives obtained from the sampled output with regard to the inputs. In fme tuning, a traditional nonlinear optinlization method is used to adjust the antecedent and consequent parameter. Finally, some examples are given to demonstrate the validity of these algorithms.

In this paper, it is proposed a tracking robust impedance controller for robots with visual feedback. It is based on a generalized impedance concept where the sensed distance is introduced as a fictitious force to the control in order to avoid obstacles in restricted motion tasks. The controller is designed to compensate for full non linear robot dynamics. Robust control law is introduced to reduce the sensibility of the control system to dynamic uncertainties of the robot and the manipulated load. It is proved that the vision control errors are ultimately bounded in the image coordinate system. Simulations are carried out to evaluate the controller performance.

Two control structures are presented for a robotic teleoperation system, including, for designing purposes, a human model in the control loop. An impedance control structure is implemented at the remote site. An adaptive impedance control structure for the remote system is proposed as well, with kinesthetic and visual feedback from the remote interaction force to the operator. Force references in both tactile and vision channels are included. This last structure lets improve the general performance of the entire teleoperation system, when either the remote robot’s load or parameters are unknown or known with uncertainties. The effects of discretizing the control algorithm and of the communication time delays between the local and remote stations, on the general stability and on the system’s performance, are analysed. Simulation results show the impedance error and force error asymptotic convergence.

A supervisory controller for a robotic teleoperation system with a long time delay. The proposed low-level control structure was designed to control the position and the interaction force between the remote manipulator and the environment. Both the human operator model and the hand controller are considered in the local station. A 2 d.o.f. direct drive robot manipulator is modelled in the remote station. The supervisory control is designed using the theory of hybrid systems so that an additional system is incorporated, which evolves according to the occurrence of uncontrolled events like communication intenuptions, etc. Simulations have been carried out to show the system's performance.

In this paper mobile robot control laws, including obstacle avoidance based on ultrasonic sensorial information are proposed. The mobile robot is assumed to evolve in a semi-structured environment. The control systems are based on the use of the extended impedance concept, in which the relationship between fictitious forces and motion error is regulated. The fictitious forces are generated from the information provided by ultrasonic sensors on the distance from the obstacle to the robot. The control algorithms also prevent from the potential problem of control command saturation. The paper includes the stability analysis of the developed control systems, using positive definite potential functions.

In this paper an adaptive controller for robot tracking using visual feedback with camerain-hand configuration is proposed. The controller is designed to compensate for full robot dynamics. Adaptation is introduced to reduce the design sensitivity due to robot and payload dynamic uncertainties. It is proved that the vision control errors are ultimately bounded in the image coordinate system. Simulations are carried out to evaluate the controller performance.

A desired dynamic behaviour of constrained manipulators can be achieved by means of impedance control. Various implementations of fixed controllers have been proposed. In this paper, an adaptive implementation is presented as an alternative to reduce the design sensitivity due to manipulator model mismatch. The adaptive controller globally achieves the impedance objective for the nonlinear dynamic model of rigid robot manipulators. Simulation results are presented to show the performance of the adaptive controller under ideal as well as actual conditions like elastic Joints, friction and algorithm discretization effects.

The didactic system developed at São Paulo University, the MFG Toolkit, consists of a simulator for control objects and a controller. In both systems it is utilized the same modeling tool, the MFG/PFS (Mark Flow Graph/Production Flow Schema), derived from Petri Nets. This modeling tool is the keystone of the MFG/PFS Methodology. The case study shown here illustrates the operation sequence for the MFG Toolkit which involves the usage of MFG/PFS Methodology for contriving a model for a given control object and a control algorithm for it.

This paper summarizes a study requested by an argentine steel plant for seamless tubes. The work is aimed to analyze, understand and propose solutions for a problem of oscillations and metal wearing found in the rack-and-pinion system which actuates the mandrel in a Continuous Mandrel Mill line. Essentially, the study comprises the mathematical modelling and programming with simulation language of the part of the system under evaluation, the analysis of present system behaviour and the proposal of solutions from the control viewpoint. As a result of this research, a proposal was implemented at the plant, attaining quite satisfactory results.

This paper presents an app.roach to feedback adaptive motion control of robot manipulators based on neural networks. The controller includes a set of trained neural networks and an update law to adjust robot dynamics and payload uncertain parameters. The controller is robust to neural networks learning errors using a sign or saturation switching function in the control law. A global stability analysis is given, as well as simulation results to show the practical feasibility and performance for the robust adaptive controller are given.

The paper considers parallel computation of an adaptive impedance control algorithm for a robot manipulator. Simulation results show that short sampling periods are necessary in order to obtain correct action of the control method. The complex control law is represented as a task graph and scheduled for computation on a network of processors. The method of scheduling is described and measured execution times are presented.

In this paper we present an adaptive hybrid impedance/force controller for rigid robot manipulators. It is based on recently developed adaptive impedance and adaptive force controllers. The hybrid control system is able to accomplish impedance objectives in free directions and force objectives in constrained directions under parametric uncertainty in robot dynamics. The proposed scheme is shown to be globally stable in the sense that the control objectives are achieved asymptotically.