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About this book

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. For years, anatomic and biomechanical studies have deepened the understanding of the human hand’s functioning and, in parallel, the robotics community has been working on the design of robotic hands capable of manipulating objects with a performance similar to that of the human hand. However, although many researchers have partially studied various aspects, to date there has been no comprehensive characterization of the human hand’s function for grasping and manipulation of everyday life objects.

This monograph explores the hypothesis that the confluence of both scientific fields, the biomechanical study of the human hand and the analysis of robotic manipulation of objects, would greatly benefit and advance both disciplines through simulation. Therefore, in this book, the current knowledge of robotics and biomechanics guides the design and implementation of a simulation framework focused on manipulation interactions that allows the study of the grasp through simulation. As a result, a valuable framework for the study of the grasp, with relevant applications in several fields such as robotics, biomechanics, ergonomics, rehabilitation and medicine, has been made available to these communities.

Table of Contents

Frontmatter

Chapter 1. Introduction

The human hand and its dexterity in grasping and manipulating objects are some of the hallmarks of the human species. Most of human mechanical interactions with the surrounding world are performed by the hands. We use our hands to perform very different tasks; from exerting high forces (e.g. using a hammer or helping each other carry heavy things) to executing very precise movements (e.g. cutting with a surgical tool or playing an instrument). We also use them to express our feelings, utilising them as a dominant part of our body language. 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 23 % of freedom [1] controlled by muscles, tendons and ligaments.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Robot Grasping Simulation

Frontmatter

Chapter 2. Robot Grasping Foundations

This chapter presents the foundations of this book, introducing the basic concepts and definitions involved in the study of object grasping and manipulation tackled in the following chapters. It starts with the definition of a grasp and the most common contact models. Then an introduction to grasp analysis and grasp synthesis is presented.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Chapter 3. 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 may provide a holistic environment to deal with the variety of aspects associated with this problem. These aspects include development and testing of new algorithms, modelling of the environments and robots, including the modelling of actuators, sensors and contacts. To fill this gap, the OpenGRASP simulation toolkit for grasping and dexterous manipulation has been developed. OpenGRASP is a new simulation toolkit, that addresses all above-mentioned aspects, and that has been developed to provide extensibility, interoperability and public availability. It 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 this chapter, the different components of OpenGRASP are presented. The core of the toolkit is an improved version of OpenRAVE, which has been enhanced with a Robot Editor and the adoption of the COLLADA file format and several plugins to enable standardization and flexibility. Tactile sensor simulation is studied in detail, proposing a new tactile sensor model which utilizes collision detection and response methods using soft contacts as well as a full friction description.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Chapter 4. Applications of Robot Grasping Simulation

We developed the OpenGRASP framework, presented in the previous chapter, as part of the work of the GRASP project. Within the project the toolkit was used as the main tool for reasoning and prediction of object properties as well as task constraints of manipulation and grasping activities executed by robots. In this chapter, these applications of the simulator in robot grasping are presented. It is demonstrated how grasp simulation is a key tool for constructing a world model and understanding the robot’s environment. Additionally, we demonstrate how to achieve a complete dynamic simulation of a humanoid robot using the developed toolkit.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Human Grasping Simulation

Frontmatter

Chapter 5. The Model of the Human Hand

In this chapter, a review of the literature regarding biomechanical and ergonomics hand models is presented. The current knowledge on hand models is used to draw out the rules for developing a realistic and self-contained biomechanical model of the hand with special emphasis on grasp and object manipulation. The proposed model consists of a scalable biomechanical model of the human hand composed of bones, tendons, muscles and skin. On this basis, we added closure algorithms to grasp virtual objects, contact models, which allow estimating the transmission of forces in the contacts, and quality indices to provide grasp evaluation tools. We have also developed a programming environment that facilitates the use of the virtual model, allowing its visualization, modification of its parameters, and thoroughly testing interactions between the model and the virtual objects. As a result, a useful tool for the study of the human hand is available to the scientific and industrial communities, with potential applications in the fields of ergonomics, prostheses design, surgery and medical rehabilitation planning.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Chapter 6. Human Grasp Evaluation

The purpose of this chapter is to present a review of the grasp quality measures that have been proposed and then the adaptation of the most common robotic grasp quality measures to the human hand grasp evaluation. Additionally, we propose complementary quality indices that may consider biomechanical aspects not taken into account by the robotic indices.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Chapter 7. Human Grasping Simulation

In this chapter, the purpose is to study the adapted grasp quality measures presented in the previous chapter in order to find the minimum set of indices that enable the evaluation of the different aspects of the human grasp on simulation. Moreover, the aim is to propose a global grasp quality index combining the different grasp aspects. Finally, this framework for grasp evaluation is used to compare the grasp capabilities of a prosthetic hand with the ones obtained with our human hand model.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru

Chapter 8. Conclusions

Grasping is one of the most challenging problems in robotics, and require knowledge and development from different fields. The problem, like many others in robotics, benefits greatly from the use of a simulator. First of all, the simulation might be used to replace the real hardware to the extent that it is capable of reproducing the actual physical behaviour, which is of special importance in the context of robot manipulation. Second, it might be used as a prediction engine that can help to understand the effects of actions and provide the base for developmental learning. Additionally, if simulation accurately reproduces the real sensor and actuator feedback, robots might automatically learn from low-level sensor inputs without the depreciation of real hardware.
Beatriz León, Antonio Morales, Joaquin Sancho-Bru
Additional information