Beatriz León

Mind the gap - robotic grasping under incomplete observation

We consider the problem of grasp and manipulation planning when the state of the world is only partially observable. Specifically, we address the task of picking up unknown objects from a table top. The proposed approach to object shape prediction aims at closing the knowledge gaps in the robots understanding of the world. A completed state estimate of the environment can then be provided to a simulator in which stable grasps and collision-free movements are planned.

OpenGRASP: a toolkit for robot grasping simulation

Simulation is essential for different robotic research fields such as mobile robotics, motion planning and grasp planning. For grasping in particular, there are no software simulation packages, which provide a holistic environment that can deal with the variety of aspects associated with this problem. These aspects include development and testing of new algorithms, modeling of the environments and robots, including the modeling of actuators, sensors and contacts. In this paper, we present a new simulation toolkit for grasping and dexterous manipulation called OpenGRASP addressing those aspects in addition to extensibility, interoperability and public availability. OpenGRASP is based on a modular architecture, that supports the creation and addition of new functionality and the integration of existing and widely-used technologies and standards. In addition, a designated editor has been created for the generation and migration of such models. We demonstrate the current state of OpenGRASPs development and its application in a grasp evaluation environment.

Evaluation of Human Prehension Using Grasp Quality Measures

One of the main features of the human hand is its grasping ability. Robot grasping has been studied for years and different quality measures have been proposed to evaluate the stability and manipulability of grasps. Although the human hand is obviously more complex than robot hands, the methods used in robotics might be adopted to study the human grasp. The purpose of this work is to propose a set of measures that allow the evaluation of different aspects of the human grasp. The most common robotic grasp quality measures have been adapted to the evaluation of the human hand and a new quality measure – the fatigue index – is proposed in order to incorporate the biomechanical aspect into the evaluation. The minimum set of indices that allows the evaluation of the different aspects of the grasp is obtained from the analysis of a human prehension experiment.

Grasp modelling with a biomechanical model of the hand

The use of a biomechanical model for human grasp modelling is presented. A previously validated biomechanical model of the hand has been used. The equilibrium of the grasped object was added to the model through the consideration of a soft contact model. A grasping posture generation algorithm was also incorporated into the model. All the geometry was represented using a spherical extension of polytopes (s-topes) for efficient collision detection. The model was used to simulate an experiment in which a subject was asked to grasp two cylinders of different diameters and weights. Different objective functions were checked to solve the indeterminate problem. The normal finger forces estimated by the model were compared to those experimentally measured. The popular objective function sum of the squared muscle stresses was shown not suitable for the grasping simulation, requiring at least being complemented by task-dependent grasp quality measures.

Task-based Grasp Adaptation on a Humanoid Robot

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa.

XPERSim: A Simulator for Robot Learning by Experimentation

In this paper, we present XPERSim, a 3D simulator built on top of open source components that enables users to quickly and easily construct an accurate and photo-realistic simulation for robots of arbitrary morphology and their environments. While many existing robot simulators provide a good dynamics simulation, they often lack the high quality visualization that is now possible with general-purpose hardware. XPERSim achieves such visualization by using the Object-Oriented Graphics Rendering Engine 3D (Ogre) engine to render the simulation whose dynamics are calculated using the Open Dynamics Engine (ODE). Through XPERSims integration into a component-based software integration framework used for robotic learning by experimentation, XPERSIF, and the use of the scene-oriented nature of the Ogre engine, the simulation is distributed to numerous users that include researchers and robotic components, thus enabling simultaneous, quasi-realtime observation of the multiple-camera simulations.

Towards a Realistic and Self-Contained Biomechanical Model of the Hand

Most of human mechanical interactions with the surrounding world are performed by the hands. They allow us to perform very different tasks; from exerting high forces (e.g. using a hammer) to executing very precise movements (e.g. cutting with a surgical tool). This versatility is possible because of a very complex constitution: a great number of bones connected through different joints, a complicated musculature and a dense nervous system. This complexity is already evident from the kinematics point of view, with more than 20 degrees of freedom (DOF) controlled by muscles, tendons and ligaments. Mathematical representations are used in order to perform qualitative or quantitative analyses on this complex reality. These representations are known as biomechanical models of the hand. In biomechanics, their use allows studying problems that cannot be analysed directly on humans or that have an experimental cost that is too high; e.g., the study of new alternatives for restoring hand pathologies. Biomechanical models are a description of the hand as a mechanical device: the different elements of the hand are defined in terms of rigid bodies, joints and actuators, and the mechanical laws are applied. As they are simplified mathematical models of the reality, their use and validity depends on the simplifications considered. The first biomechanical models of the hand were developed to explain and clarify the functionality of different anatomical elements. In this regard, we can find many works that studied the function of the intrinsic muscles (Leijnse & Kalker, 1995; Spoor, 1983; Spoor & Landsmeer, 1976; Storace & Wolf, 1979, 1982; Thomas et al., 1968) and many others that tried to give an insight into the movement coordination of the interphalangeal joints (Buchner et al., 1988; Lee & Rim, 1990). Models for studying the causes and effects of different pathologies of the hand also appeared early on, such as the swan neck and boutonniere deformities or the rupture of the triangular ligament or the volar displacement of the extensor tendon (Smith et al., 1964; Storace & Wolf, 1979, 1982). All these models were, though, very limited, twodimensional models allowing only the study of flexion-extension movements, they modelled only one finger, and they included important simplifications. By the year 2000, few threedimensional models had been developed (Biryukova & Yourovskaya, 1994; Casolo & Lorenzi,

Evaluation of prosthetic hands prehension using grasp quality measures

Prosthetic hands have evolved and improved over the years, helping people gaining manipulation capabilities. Having a simulation tool able to obtain quantitative evaluation of the grasp capabilities of such hands could give insights as how to improve the design of hand prostheses or robotic hands by means of obtaining better quality scores. The purpose of this work is to present a framework developed to evaluate the grasp capabilities of a prosthetic hand using a selected set of grasp quality measures, and compare the results with the ones obtained for the human hand using a biomechanical model. Experiments grasping an object with different postures and varying aspects of the prosthetic hand model were performed showing the functionality of the proposed framework to evaluate the grasp quality.

Model of tactile sensors using soft contacts and its application in robot grasping simulation

In the context of robot grasping and manipulation, realistic dynamic simulation requires accurate modeling of contacts between bodies and, in a practical level, accurate simulation of touch sensors. This paper addresses the problem of creating a simulation of a tactile sensor as well as its implementation in a simulation environment. The simulated tactile sensor model utilizes collision detection and response methods using soft contacts as well as a full friction description. The tactile element is created based on a geometry enabling the creation of a variety of different shape tactile sensors. The tactile sensor element can be used to detect touch against triangularized geometries. This independence in shape enables the use of the sensor model for various applications, ranging from regular tactile sensors to more complex geometries as the human hand which makes it possible to explore human-like touch. The developed tactile sensor model is implemented within OpenGRASP and is available in the open-source plugin. The model has been validated through several experiments ranging from physical properties verification to testing on robot grasping applications. This simulated sensor can provide researchers with a valuable tool for robotic grasping research, especially in cases where the real sensors are not accurate enough yet.

A Software System for Robotic Learning by Experimentation

The goal of this work is to develop an integration framework for a robotic software system which enables robotic learning by experimentation within a distributed and heterogeneous setting. To meet this challenge, the authors specified, defined, developed, implemented and tested a component-based architecture called XPERSIF. The architecture comprises loosely-coupled, autonomous components that offer services through their well-defined interfaces and form a service-oriented architecture. The Ice middleware is used in the communication layer. Additionally, the successful integration of the XPERSim simulator into the system has enabled simultaneous quasi-realtime observation of the simulation by numerous, distributed users.