Most exoskeleton designs rely on structures and mechanical joints that do not guarantee the right match between the orthosis and the user. This paper proposes a virtual joint model based on three active degrees of freedom aimed to emulate a human joint. This joint is capable of performing a dynamic servo-adaptation in real-time to avoid misalignments and to provide a flexible adjustment to different users' sizes in order to avoid undesirable interaction forces.

This paper presents a study on how the application of scaling techniques to an interface affects its performance. A progressive scaling factor based on the position and velocity of the cursor and the targets improves the efficiency of an interface, thereby reducing the user's workload. The study uses several human-motor models to interpret human intention and thus contribute to defining and adapting the scaling parameters to the execution of the task. Two techniques addressed to vary the control-display ratio are compared, and a new method for aiding in the task of steering is proposed.

In order to enable robots to work in close contact with humans or in environments with unknown obstacles, new reactive control strategies based on sensitive bumper skins are proposed. The aim of this work is to provide a robot with contact and force control based strategies that make it dependable, safe and with foreseeable behaviours. The sensory skin is composed of rigid-bumpers provided with deformation sensors incorporated in a flexible substrate. This solution is a compromise between a simple bumper skin and current array-based robot skins, with better potential performances but, more costly and with usability problems. Such sensitive bumpers cover all moveable links of the robot allowing the detection of collisions, measuring the force involved and locating the point of contact with reasonable precision and cost

This paper presents a manipulation and measurement aid for tasks carried out in micro-nano environments operating with scanning AFM. In teleoperated manipulation or measurement over a given point of the target, where a slow and precise movement is necessary, the developed system increases the accuracy in this point producing a space deformation. In automatic scanning, the adjusted selection of the target, through assisted image segmentation, enables to reduce the working time.

Teleoperation solves several difficulties that current robots can not overcome. The intervention of a human operator in deciding the strategies required to perform some given tasks allows robots to carry out operations in dangerous environments or in areas inaccessible to humans. Despite such task becomes feasible, it is necessary to use methods that assist the operator in its manipulation. This paper describes a method for assisting teleoperation, which is based on the dynamic variation of the scale of the working space to improve the movement precision near the point of interest.

As robotics evolves towards application fields in which humans cooperate with robots, working closer and closer, the requirements for human robot interactions increase. This paper presents new advances in gesture based guidance and control of a robot in assistant tasks. The work described includes the integration of force and vision for the quantitative and qualitative appreciation of human intention and the robot behaviors to respond in real time to these human orders.

Teleoperation makes possible the execution of many tasks, that otherwise are not feasible when a human operator can not access to the working area due to dangerousness or environmental conditions, and it is not possible as well, to program the task so as to be performed autonomously, due to its complexity. Nevertheless, manipulation tasks require certain ability from the human operator due to the difficulties that produce the need to operate through control devices that does not fit with the structure of the slave arms. With the aim of increasing the precision capabilities provided by such control interfaces, a vision based procedure designed to deform the space around the working point has been developed. The vision system operates from the detection of the relevant scene elements. This space deformation produces automatically a progressive increase in precision when the robot arm approaches the relevant detected elements.

The analysis of the error of stereo measurements by triangulation is revisited from three points of view: geometrical, statistical and visual quality. When the target is visible by a set of distributed cameras in the workspace, there are multiple combinations of camera pairs adequate to be considered for the location, by triangulation, of the target position. Three-camera placements are analysed evaluating their precision in a short-medium distance. The work presented analyses which combination of stereo measurements gives the best results, and proposes a method for the automatic selection of the most adequate cameras pair.

Teleoperation in harsh environments has to tackle the problem of working with images of poor quality, as the visual feedback means for the human operator. This paper describes a procedure for image augmentation, based on the models of the scene elements, which are built from the images acquired in a previous phase, before the execution of the task, when the visual environment conditions are still good enough.

The aim of the work is to determine the best landmark for its use in tasks such as precise positioning of AGVs or mobile robots in front of loading/unloading areas. The work developed aims at determining the precision that can be achieved with different pattern landmarks, of use in positioning systems, based on computer vision. Different computer vision algorithms have been tested from the images acquired from different camera configurations and bending angles with respect to the vertical axis. As a result of the evaluation of these errors, we extract the recommendation of the most favourable bicolour pattern to be used, as well as the bounding errors obtained from the segmentation and recognition methods most frequently used.

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle.

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments.

We present a processor that, attached to a PC main board acts as an image associative memory. The main contribution is that the operation time required to recognize an object remains constant regardless of the number of stored models. The object silhouette is used as the key image feature allowing us to recognize 2D or 3D objects from a single viewpoint. The recognition method is based on a template matching operation in order to simplify the processor architecture and to achieve a 8 objects per second recognition rate. Digital but also analog techniques have been used in the processor design. Both the architecture and the processing algorithm are presented as well as results with real images.

This paper faces up the problem of carrying out simple tasks, such as to fasten an object, tasks that become relatively complex in operations using robots, specially in underwater environments. The goal of this work is to perform such tasks by using intelligent strategies that plan step by step allowing for compensation of the robots own limitations. The strategy is based on the use of information from stereo vision and the required auxiliary devices or tools to contribute to the development of the task.

A robotic system developed to manipulate ophthalmic lenses during the edging process is presented. The robot is assisted by a machine vision system to accurately determine the position and orientation of the lens' optical center and axis, through the localization of two small fiducial marks on the lens surface. The optimal design of the fiducial marks is investigated in order to minimize their size. It is shown that a regular diamond is the most detectable shape at minimum sizes. Three different camera placement strategies are discussed, taking into account accuracy constraints and calibration requirements. The chosen solution uses a camera attached to the robot end-effector. The robotic system proves to be advantageous with respect to the manual process, substantially improving the final accuracy while maintaining or even reducing the cycle time.

A robotic arm which automatically guides the camera in the laparoscopic surgery is presented. The goal of this work is to generate adequate camera control strategies to track the working scene during a surgical procedure. The system is based on the computer vision analysis of the laparoscopic image that allows the surgeon to identify the scene's relevant point from the surgical instruments.

The vision system developed is based on the addition of 3D information of some preselected points of the 2D image of the scene in such a way that the system is able not only to recognize the part but also to have a rough description of its location in the 3D space which in general means improving the global performance of the vision system for Robotics applications. The method used to get the depth information is "motion stereo". The two techniques proposed to improve resolution of the stereoscopic system developed are based on, on the one hand, increasing the base line (distance between the initial and the final point of view) and on the other hand performing several depth measurements and getting the final value by averaging.

The first results of a vision system which adds to a 2D image the depth information of certain points are presented. The goal of the system is to provide the control unit of a robot with an approximate 3D description of the industrial part to be manipulated or of the working area. Depth information about the selected points of the scene is obtained by stereo vision. The determination of disparity is solved by changing the point of view of the TV camera employed by means of two oscillating mirrors which allow continuous tracking of the selected points. A specialized image processor has been designed to deal with the tasks of selection of outstanding points of objects (vertices) and continuous tracking of these points between consecutive images when displacing the mirrors in order to obtain a short time of calculation as well as a low cost system. That way at the end of each sweep of the mirrors we get the information needed to solve triangulation from pairs of homologe points. The time spent to get the three dimensional information of the scene is about one second, which corresponds to the time need to get enough intermediate images to guarantee the correct tracking of vertices.

The vision system described below has the aim of recognizing objects on the plane by means of the binary information of their contour. The object's description consist of a sequence of curvatures which is obtained by contour tracking. The recognizing process is based on the measure of similitude between sequences corresponding to the analized object and to models memorized in a previous training phase. The vision system consists of a specialized circuit allowing the obtention of the object contour using a gradient operator, and a low cost microcomputer which is able to recognize the object and to calculate its orientation.