Pablo Gil

Virtual disassembly of products based on geometric models

This paper describes different aspects of a disassembly system and presents the information model to obtain, on the one hand, the movements necessary for removing a component, and, on the other, a simulation of the disassembly process carried out. The inputs of the disassembly system are the CAD model of the product to be disassembled and the different features of the components stored in a database. Based on such information, an object-oriented model required for developing the disassembly process in a flexible way is generated. Local and global strategies for the removal of one component, using a set of translational movements, are described. Finally, the paper describes a simulation system that allows the verification of the disassembly movements automatically obtained, and simultaneously, to determine the ease of non-destructive disassembly.

Flexible multi-sensorial system for automatic disassembly using cooperative robots

Flexible multisensorial systems are a very important issue in the current industry when disassembling and recycling tasks have to be performed. These tasks can be performed by a human operator or by a robot system. In the current paper a robotic system to perform the required tasks is presented. This system takes into consideration the distribution of the necessary tasks to perform the disassembly of a component using several robots in a parallel or in a cooperative way. The algorithm proposed to distribute the task among robots takes into consideration the characteristics of each task and the sequence that needs to be followed to perform the required disassembly of the product. Furthermore, this paper presents a disassembly system based on a sensorized cooperative robots interaction framework for the planning of movements and detections of objects in the disassembly tasks. To determine the sequence of the disassembly of some products, a new strategy to distribute a set of tasks among robots is presented. Subsequently, the visual detection system used for detecting targets and characteristics is described. To carry out this detection process, different well known strategies, such as matching templates, polygonal approach and edge detection, are applied. Finally, a visual-force control system has been implemented in order to track disassembly trajectories. An important aspect of this system is the processing of the sensorial information in order to guarantee coherence. This aspect allows the application of both sensors, visual and force sensors, co-ordinately to disassembly tasks. The proposed system is validated by experiments using several types of components such as the covers of batteries and electronic circuits from toys, and drives and screws from PCs.

EJS+EjsRL: An interactive tool for industrial robots simulation, Computer Vision and remote operation

This paper presents an interactive Java software platform which enables users to easily create advanced robotic applications together with Computer Vision processing. This novel tool is composed of two layers: (1) Easy Java Simulations (EJS), an open-source tool which provides support for creating applications with a full 2D/3D interactive graphical interface, and (2) EjsRL, a high-level Java library specifically designed for EJS which provides a complete functional framework for modeling and simulation of arbitrary serial-link manipulators, Computer Vision algorithms and remote operation. The combination of both components sets up a software architecture which contains a high number of functionalities in the same platform to develop complex simulations in Robotics and Computer Vision fields. In addition, the paper shows its successful application to virtual and remote laboratories, web-based resources that enhance the accessibility of experimental setups for education and research.

3D Visual Sensing of the Human Hand for the Remote Operation of a Robotic Hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

Visual control of robots using range images.

In the last years, 3D-vision systems based on the time-of-flight (ToF) principle have gained more importance in order to obtain 3D information from the workspace. In this paper, an analysis of the use of 3D ToF cameras to guide a robot arm is performed. To do so, an adaptive method to simultaneous visual servo control and camera calibration is presented. Using this method a robot arm is guided by using range information obtained from a ToF camera. Furthermore, the self-calibration method obtains the adequate integration time to be used by the range camera in order to precisely determine the depth information.

A cooperative robotic system based on multiple sensors to construct metallic structures.

This paper describes a multisensorial robotic system to automatically construct metallic structures. Two robots must work cooperatively in the same workspace to perform the task. The robots are automatically guided using visual and force sensor information. A new time-independent visual force control system which guarantees the adequate robot behaviour during the construction of the structure is described. During the construction of the structure, a human operator works cooperatively with the robots in order to perform some tasks which cannot be automatically developed by the robots. To do so, a new human–robot cooperation approach is described in order to guarantee the human safety. The correct behaviour of the different subsystems proposed in the paper is demonstrated in Section 6 by the construction of a real structure composed of several metallic tubes and different types of pieces to join them.

Improving detection of surface discontinuities in visual-force control systems

In this paper, a new approach to detect surface discontinuities in a visual-force control task is described. A task which consists in tracking a surface using visual-force information is shown. In this task, in order to reposition the robot tool with respect to the surface it is necessary to determine the surface discontinuities. This paper describes a new method to detect surface discontinuities employing sensorial information obtained from a force sensor, a camera and structured light. This method has proved to be more robust than previous systems even in situations where high frictions occur.

Gaussian noise elimination in colour images by vector-connected filters

This paper deals with the use of vector-connected filters for eliminating Gaussian noise in colour images. This class of morphological filters suppresses noise but preserves the contours of the objects. We impose a total order between pixels for morphological processing. Once the HSI space has been adapted, we employ it in the lexicographical order. As such, all of the morphological operations are vectorial. After having defined the vectorial geodesic operators, they are then employed to eliminate Gaussian noise.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Analysis of Shapes to Measure Surfaces

This paper presents a method to analyse 3D planar surfaces and to measure variations on it. The method is oriented to the detection of deformations on the elastic object surfaces formed by flat faces. These deformations are usually caused when two bodies, a solid and another elastic object, come in contact and there are contact pressures among their faces. Our method describes a strategy to model the shape of deformation using a mathematical approach based on two concepts: Histogram and Map of curvature. In particular, we describe the algorithm for deformations in order to use it in visual control and inspection tasks for manipulation processes with robot hands. Several experiments and their results are shown to evaluate the validity and robustness of the method to detect and measure deformations in grasping tasks. To do it, some virtual scenarios were created to simulate contacts with fingers of a hand robot.