Aerospace medicine and biology: A continuing bibliography with indexes (supplement 331)

This bibliography lists 129 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during December, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Self-Contained and Automatic Calibration of a Multi-Fingered Hand Using Only Pairwise Contact Measurements

A self-contained calibration procedure that can be performed automatically without additional external sensors or tools is a significant advantage, especially for complex robotic systems. Here, we show that the kinematics of a multi-fingered robotic hand can be precisely calibrated only by moving the tips of the fingers pairwise into contact. The only prerequisite for this is sensitive contact detection, e.g., by torque-sensing in the joints (as in our DLR-Hand II) or tactile skin. The measurement function for a given joint configuration is the distance between the modeled fingertip geometries, but the actual measurement is always zero. In an in-depth analysis, we prove that this contact-based calibration determines all quantities needed for manipulating objects with the hand, i.e., the difference vectors of the fingertips, and that it is as sensitive as a calibration using an external visual tracking system and markers. We describe the complete calibration scheme, including the selection of optimal sample joint configurations and search motions for the contacts despite the initial kinematic uncertainties. In a real-world calibration experiment for the torque-controlled four-fingered DLR-Hand II, the maximal error of 17.7mm can be reduced to only 3.7mm.Comment: Presented at the 2023 IEEE-RAS International Conference on Humanoid Robot

Towards comprehensive capture of human grasping and manipulation skills

Grasping plays a central role in our daily life. To interact with objects surrounding them, people use a large diversity of hand configurations in combination with forces ranging from the small ones involved in manipulating a pen for writing, to larger forces such as when drinking a cup full of water, and even larger ones such as when wielding a hammer. In this paper we present a setup to capture human hand configuration and motion as well as the forces applied by the hand on objects while performing a task. Hand configuration is obtained through the use of a data glove device while interaction forces are measured through an array of tactile sensors. Current approaches in the state-of-the-art are limited in that they only measure interaction forces on the fingers or the palm, ignoring the important role of the sides of the fingers in achieving a grasp/manipulation task. We propose a new setup for a “sensorized” data glove to address these limitations and through which a more complete picture of human hand response in grasping and manipulation can be obtained. This setup was successfully tested on five subjects performing a variety of different tasks

Génération de trajectoires de manipulation d'objets à l'aide d'un exosquelette isomorphe à la main mécanique à 16 ddl du LMS

Ce papier concerne le développement et la mise en oeuvre d'un exosquelette particulier que nous avons développé pour la main mécanique à 16 ddl du LMS. Celui-ci possède une architecture cinématique et des dimensions identiques à cette main mécanique. Cette particularité permet d'obtenir très rapidement et très facilement des trajectoires de manipulation pour leur exécution par la main mécanique. Nous présentons cet exosquelette, l'interface graphique et la méthode développée pour déterminer les coordonnées opérationnelles de l'objet pendant cette phase d'apprentissage afin de synchroniser graphiquement le mouvement de l'objet avec celui des doigts tout en s'affranchissant de capteurs extéroceptifs. Enfin nous donnons un exemple de trajectoire de référence obtenue à partir de l'exosquelette et reproduite avec succès graphiquement et par la main mécanique

On Computing Task-Oriented Grasps

This paper addresses the problem of optimal grasping of an object with a multi-fingered robotic hand for accomplishing a given task. The task is first demonstrated by a human operator and its force/torque requirements are captured through the usage of a sensorized tool. The grasp quality is computed through a task compatibility criterion. Grasp synthesis is then formulated as a single constrained optimization problem, generating grasps that are feasible for the hand’s kinematics by maximizing the corresponding task-oriented quality criterion and ensuring grasp stability. The method was validated on a human hand model and is shown to be easily adapted to different hand kinematic models

Design and Evaluation of a Contact-Free Interface for Minimally Invasive Robotics Assisted Surgery

Robotic-assisted minimally invasive surgery (RAMIS) is becoming increasingly more common for many surgical procedures. These minimally invasive techniques offer the benefit of reduced patient recovery time, mortality and scarring compared to traditional open surgery. Teleoperated procedures have the added advantage of increased visualization, and enhanced accuracy for the surgeon through tremor filtering and scaling down hand motions. There are however still limitations in these techniques preventing the widespread growth of the technology. In RAMIS, the surgeon is limited in their movement by the operating console or master device, and the cost of robotic surgery is often too high to justify for many procedures. Sterility issues arise as well, as the surgeon must be in contact with the master device, preventing a smooth transition between traditional and robotic modes of surgery. This thesis outlines the design and analysis of a novel method of interaction with the da Vinci Surgical Robot. Using the da Vinci Research Kit (DVRK), an open source research platform for the da Vinci robot, an interface was developed for controlling the robotic arms with the Leap Motion Controller. This small device uses infrared LEDs and two cameras to detect the 3D positions of the hand and fingers. This data from the hands is mapped to the da Vinci surgical tools in real time, providing the surgeon with an intuitive method of controlling the instruments. An analysis of the tracking workspace is provided, to give a solution to occlusion issues. Multiple sensors are fused together in order to increase the range of trackable motion over a single sensor. Additional work involves replacing the current viewing screen with a virtual reality (VR) headset (Oculus Rift), to provide the surgeon with a stereoscopic 3D view of the surgical site without the need for a large monitor. The headset also provides the user with a more intuitive and natural method of positioning the camera during surgery, using the natural motions of the head. The large master console of the da Vinci system has been replaced with an inexpensive vision based tracking system, and VR headset, allowing the surgeon to operate the da Vinci Surgical Robot with more natural movements for the user. A preliminary evaluation of the system is provided, with recommendations for future work

Kinematic Model of the Hand using Computer Vision

La biotecnología es una ciencia en auge y en especial el diseño de interfaces humano-máquina. El objetivo de este proyecto es avanzar en dicho campo y en concreto explorar el diseño de exoesqueletos y prótesis de la mano humana. La metodología utilizada en este proyecto fundamentalmente consta de tres fases. En primer lugar, se ha establecido un modelo teórico de la cinemática de la mano recurriendo a la documentación médica especializada para concretar su anatomía. Posteriormente se ha procedido a sintetizar la mano en sus parámetros simplificados y así definir un modelo robótico. Para ajustar dicho modelo a una mano real se procede a capturar el movimiento de esta en una secuencia de imágenes mediante ordenador. Para ello se utilizan unas marcas en las uñas de la mano con una geometría específica de tal manera que permite la estimación de su pose, es decir su posición e orientación, en el espacio. Esta secuencia de poses estimadas permite caracterizar el movimiento completo de la mano. Por último, mediante la síntesis cinemática dimensional, se definen las ecuaciones de movimiento parametrizadas del modelo teórico de la mano. Estas ecuaciones permiten ajustar el modelo a la secuencia de poses estimadas mediante visión por ordenador y así crear un modelo personalizado de la mano. Gracias a este sistema, se puede realizar un estudio sobre la correspondencia entre señales electomiográficas y los movimientos de la mano y así lograr una mejor funcionalidad de las prótesis. En definitiva, este proyecto ha logrado diseñar un algoritmo robusto para el seguimiento y estimación de las poses de las uñas de las manos y ha conseguido definir las ecuaciones de movimiento y crear una aplicación para resolverlas. Asimismo, ha encontrado modelos no antropomórficos que podrían ser de utilidad en el diseño de exoesqueletos

Modelado de sensores piezoresistivos y uso de una interfaz basada en guantes de datos para el control de impedancia de manipuladores robóticos

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Arquitectura de Computadores y Automática, leída el 21-02-2014Sección Deptal. de Arquitectura de Computadores y Automática (Físicas)Fac. de Ciencias FísicasTRUEunpu