Intelligent gripper design and application for automated part recognition and gripping

Intelligent gripping may be achieved through gripper design, automated part recognition, intelligent algorithm for control of the gripper, and on-line decision-making based on sensory data. A generic framework which integrates sensory data, part recognition, decision-making and gripper control to achieve intelligent gripping based on ABB industrial robot is constructed. The three-fingered gripper actuated by a linear servo actuator designed and developed in this project for precise speed and position control is capable of handling a large variety of objects. Generic algorithms for intelligent part recognition are developed. Edge vector representation is discussed. Object geometric features are extracted. Fuzzy logic is successfully utilized to enhance the intelligence of the system. The generic fuzzy logic algorithm, which may also find application in other fields, is presented. Model-based gripping planning algorithm which is capable of extracting object grasp features from its geometric features and reasoning out grasp model for objects with different geometry is proposed. Manipulator trajectory planning solves the problem of generating robot programs automatically. Object-oriented programming technique based on Visual C++ MFC is used to constitute the system software so as to ensure the compatibility, expandability and modular programming design. Hierarchical architecture for intelligent gripping is discussed, which partitions the robot’s functionalities into high-level (modeling, recognizing, planning and perception) layers, and low-level (sensing, interfacing and execute) layers. Individual system modules are integrated seamlessly to constitute the intelligent gripping system

Trajectory generation of space telerobots

The purpose is to review a variety of trajectory generation techniques which may be applied to space telerobots and to identify problems which need to be addressed in future telerobot motion control systems. As a starting point for the development of motion generation systems for space telerobots, the operation and limitations of traditional path-oriented trajectory generation approaches are discussed. This discussion leads to a description of more advanced techniques which have been demonstrated in research laboratories, and their potential applicability to space telerobots. Examples of this work include systems that incorporate sensory-interactive motion capability and optimal motion planning. Additional considerations which need to be addressed for motion control of a space telerobot are described, such as redundancy resolution and the description and generation of constrained and multi-armed cooperative motions. A task decomposition module for a hierarchical telerobot control system which will serve as a testbed for trajectory generation approaches which address these issues is also discussed briefly

Kinematic Analysis of Multi-Fingered, Anthropomorphic Robotic Hands

The ability of stable grasping and fine manipulation with the multi-fingered robot hand with required precision and dexterity is playing an increasingly important role in the applications like service robots, rehabilitation, humanoid robots, entertainment robots, industries etc.. A number of multi-fingered robotic hands have been developed by various researchers in the past. The distinct advantages of a multi-fingered robot hand having structural similarity with human hand motivate the need for an anthropomorphic robot hand. Such a hand provides a promising base for supplanting human hand in execution of tedious, complicated and dangerous tasks, especially in situations such as manufacturing, space, undersea etc. These can also be used in orthopaedic rehabilitation of humans for improving the quality of the life of people having orthopedically and neurological disabilities. The developments so far are mostly driven by the application requirements. There are a number of bottlenecks with industrial grippers as regards to the stability of grasping objects of irregular geometries or complex manipulation operations. A multi-fingered robot hand can be made to mimic the movements of a human hand. The present piece of research work attempts to conceptualize and design a multi-fingered, anthropomorphic robot hand by structurally imitating the human hand. In the beginning, a brief idea about the history, types of robotic hands and application of multi-fingered hands in various fields are presented. A review of literature based on different aspects of the multi-fingered hand like structure, control, optimization, gasping etc. is made. Some of the important and more relevant literatures are elaborately discussed and a brief analysis is made on the outcomes and shortfalls with respect to multi-fingered hands. Based on the analysis of the review of literature, the research work aims at developing an improved anthropomorphic robot hand model in which apart from the four fingers and a thumb, the palm arch effect of human hand is also considered to increase its dexterity. A robotic hand with five anthropomorphic fingers including the thumb and palm arch effect having 25 degrees-of-freedom in all is investigated in the present work. Each individual finger is considered as an open loop kinematic chain and each finger segment is considered as a link of the manipulator. The wrist of the hand is considered as a fixed point. The kinematic analyses of the model for both forward kinematics and inverse kinematic are carried out. The trajectories of the tip positions of the thumb and the fingers with respect to local coordinate system are determined and plotted. This gives the extreme position of the fingertips which is obtained from the forward kinematic solution with the help of MATLAB. Similarly, varying all the joint iv angles of the thumb and fingers in their respective ranges, the reachable workspace of the hand model is obtained. Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for solving the inverse kinematic problem of the fingers. Since the multi-fingered hand grasps the object mainly through its fingertips and the manipulation of the object is facilitated by the fingers due to their dexterity, the grasp is considered to be force-closure grasp. The grasping theory and different types of contacts between the fingertip and object are presented and the conditions for stable and equilibrium grasp are elaborately discussed. The proposed hand model is simulated to grasp five different shaped objects with equal base dimension and height. The forces applied on the fingertip during grasping are calculated. The hand model is also analysed using ANSYS to evaluate the stresses being developed at various points in the thumb and fingers. This analysis was made for the hand considering two different hand materials i.e. aluminium alloy and structural steel. The solution obtained from the forward kinematic analysis of the hand determines the maximum size for differently shaped objects while the solution to the inverse kinematic problem indicates the configurations of the thumb and the fingers inside the workspace of the hand. The solutions are predicted in which all joint angles are within their respective ranges. The results of the stress analysis of the hand model show that the structure of the fingers and the hand as a whole is capable of handling the selected objects. The robot hand under investigation can be realized and can be a very useful tool for many critical areas such as fine manipulation of objects, combating orthopaedic or neurological impediments, service robotics, entertainment robotics etc. The dissertation concludes with a summary of the contribution and the scope of further work

Design, development and evaluation of Stanford/Ames Extra-Vehicular Activity (EVA) prehensors

A summary is given of progress to date on work proposed in 1983 and continued in 1985, including design iterations on three different types of manually powered prehensors, construction of functional mockups of each and culminating in detailed drawings and specifications for suit-compatible sealed units for testing under realistic conditions

Robotic hand controlled based on flexible sensor by glove using wireless communication

A humanoid robot's hand is a vital component. It's tough to create an action that looks like a human side. This study suggested a similar-sized and light-weight robotic hand and investigated the possibility of controlling based on flexible sensor by glove using wireless communication. The robotic hand is built to manoeuvre and function like a human hand. One of the robot hand's fingers has three degrees of freedom, nearly identical to a human finger. When the fingers of the manipulator switch, the glove using wireless communication sends a feedback signal to the microcontroller. Each robot hand's finger sector is powered by a Servo Motor chain drive. Furthermore, since the servo motor can only supply a low torque for the finger, the robot hand can only produce a force that is appropriate for each finger. Arduino Mega monitor the robot's entire behaviour and activity. The robot hand is managed in real time by the glove using wireless communication. As a result, it may perform tasks similar to those performed by a human hand, such as gripping an object. The robot hand will be used to implement humanoid robots with further research and developmen

Control Techniques for Robot Manipulator Systems with Modeling Uncertainties

This dissertation describes the design and implementation of various nonlinear control strategies for robot manipulators whose dynamic or kinematic models are uncertain. Chapter 2 describes the development of an adaptive task-space tracking controller for robot manipulators with uncertainty in the kinematic and dynamic models. The controller is developed based on the unit quaternion representation so that singularities associated with the otherwise commonly used three parameter representations are avoided. Experimental results for a planar application of the Barrett whole arm manipulator (WAM) are provided to illustrate the performance of the developed adaptive controller. The controller developed in Chapter 2 requires the assumption that the manipulator models are linearly parameterizable. However there might be scenarios where the structure of the manipulator dynamic model itself is unknown due to difficulty in modeling. One such example is the continuum or hyper-redundant robot manipulator. These manipulators do not have rigid joints, hence, they are difficult to model and this leads to significant challenges in developing high-performance control algorithms. In Chapter 3, a joint level controller for continuum robots is described which utilizes a neural network feedforward component to compensate for dynamic uncertainties. Experimental results are provided to illustrate that the addition of the neural network feedforward component to the controller provides improved tracking performance. While Chapter\u27s 2 and 3 described two different joint controllers for robot manipulators, in Chapter 4 a controller is developed for the specific task of whole arm grasping using a kinematically redundant robot manipulator. The whole arm grasping control problem is broken down into two steps; first, a kinematic level path planner is designed which facilitates the encoding of both the end-effector position as well as the manipulators self-motion positioning information as a desired trajectory for the manipulator joints. Then, the controller described in Chapter 3, which provides asymptotic tracking of the encoded desired joint trajectory in the presence of dynamic uncertainties is utilized. Experimental results using the Barrett Whole Arm Manipulator are presented to demonstrate the validity of the approach

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 344)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 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

Planning and estimation algorithms for human-like grasping

Mención Internacional en el título de doctorThe use of robots in human-like environments requires them to be able to sense and model unstructured scenarios. Thus, their success will depend on their versatility for interacting with the surroundings. This interaction often includes manipulation of objects for accomplishing common daily tasks. Therefore, robots need to sense, understand, plan and perform; and this has to be a continuous loop. This thesis presents a framework which covers most of the phases encountered in a common manipulation pipeline. First, it is shown how to use the Fast Marching Squared algorithm and a leader-followers strategy to control a formation of robots, simplifying a high dimensional path-planning problem. This approach is evaluated with simulations in complex environments in which the formation control technique is applied. Results are evaluated in terms of distance to obstacles (safety) and the needed deformation. Then, a framework to perform the grasping action is presented. The necessary techniques for environment modelling and grasp synthesis and path planning and control are presented. For the motion planning part, the formation concept from the previous chapter is recycled. This technique is applied to the planning and control of the movement of a complex hand-arm system. Tests using robot Manfred show the possibilities of the framework when performing in real scenarios. Finally, under the assumption that the grasping actions may not always result as it was previously planned, a Bayesian-based state-estimation process is introduced to estimate the final in-hand object pose after a grasping action is done, based on the measurements of proprioceptive and tactile sensors. This approach is evaluated in real experiments with Reex Takktile hand. Results show good performance in general terms, while suggest the need of a vision system for a more precise outcome.La investigación en robótica avanza con la intención de evolucionar hacia el uso de los robots en entornos humanos. A día de hoy, su uso está prácticamente limitado a las fábricas, donde trabajan en entornos controlados realizando tareas repetitivas. Sin embargo, estos robots son incapaces de reaccionar antes los más mínimos cambios en el entorno o en la tarea a realizar. En el grupo de investigación del Roboticslab se ha construido un manipulador móvil, llamado Manfred, en el transcurso de los últimos 15 años. Su objetivo es conseguir realizar tareas de navegación y manipulación en entornos diseñados para seres humanos. Para las tareas de manipulación y agarre, se ha adquirido recientemente una mano robótica diseñada en la universidad de Gifu, Japón. Sin embargo, al comienzo de esta tesis, no se había realzado ningún trabajo destinado a la manipulación o el agarre de objetos. Por lo tanto, existe una motivación clara para investigar en este campo y ampliar las capacidades del robot, aspectos tratados en esta tesis. La primera parte de la tesis muestra la aplicación de un sistema de control de formaciones de robots en 3 dimensiones. El sistema explicado utiliza un esquema de tipo líder-seguidores, y se basa en la utilización del algoritmo Fast Marching Square para el cálculo de la trayectoria del líder. Después, mientras el líder recorre el camino, la formación se va adaptando al entorno para evitar la colisión de los robots con los obstáculos. El esquema de deformación presentado se basa en la información sobre el entorno previamente calculada con Fast Marching Square. El algoritmo es probado a través de distintas simulaciones en escenarios complejos. Los resultados son analizados estudiando principalmente dos características: cantidad de deformación necesaria y seguridad de los caminos de los robots. Aunque los resultados son satisfactorios en ambos aspectos, es deseable que en un futuro se realicen simulaciones más realistas y, finalmente, se implemente el sistema en robots reales. El siguiente capítulo nace de la misma idea, el control de formaciones de robots. Este concepto es usado para modelar el sistema brazo-mano del robot Manfred. Al igual que en el caso de una formación de robots, el sistema al completo incluye un número muy elevado de grados de libertad que dificulta la planificación de trayectorias. Sin embargo, la adaptación del esquema de control de formaciones para el brazo-mano robótico nos permite reducir la complejidad a la hora de hacer la planificación de trayectorias. Al igual que antes, el sistema se basa en el uso de Fast Marching Square. Además, se ha construido un esquema completo que permite modelar el entorno, calcular posibles posiciones para el agarre, y planificar los movimientos para realizarlo. Todo ello ha sido implementado en el robot Manfred, realizando pruebas de agarre con objetos reales. Los resultados muestran el potencial del uso de este esquema de control, dejando lugar para mejoras, fundamentalmente en el apartado de la modelización de objetos y en el cálculo y elección de los posibles agarres. A continuación, se trata de cerrar el lazo de control en el agarre de objetos. Una vez un sistema robótico ha realizado los movimientos necesarios para obtener un agarre estable, la posición final del objeto dentro de la mano resulta, en la mayoría de las ocasiones, distinta de la que se había planificado. Este hecho es debido a la acumulación de fallos en los sistemas de percepción y modelado del entorno, y los de planificación y ejecución de movimientos. Por ello, se propone un sistema Bayesiano basado en un filtro de partículas que, teniendo en cuenta la posición de la palma y los dedos de la mano, los datos de sensores táctiles y la forma del objeto, estima la posición del objeto dentro de la mano. El sistema parte de una posición inicial conocida, y empieza a ejecutarse después del primer contacto entre los dedos y el objeto, de manera que sea capaz de detectar los movimientos que se producen al realizar la fuerza necesaria para estabilizar el agarre. Los resultados muestran la validez del método. Sin embargo, también queda claro que, usando únicamente la información táctil y de posición, hay grados de libertad que no se pueden determinar, por lo que, para el futuro, resultaría aconsejable la combinación de este sistema con otro basado en visión. Finalmente se incluyen 2 anexos que profundizan en la implementación de la solución del algoritmo de Fast Marching y la presentación de los sistemas robóticos reales que se han usado en las distintas pruebas de la tesis.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Carlos Balaguer Bernaldo de Quirós.- Secretario: Raúl Suárez Feijoo.- Vocal: Pedro U. Lim

The 2nd Conference on Remotely Manned Systems (RMS): Technology and Applications

Control theory and the design of manipulators, teleoperators, and robots are considered. Applications of remotely manned vehicles to space maintenance and orbital assembly, industry and productivity, undersea operations, and rehabilitation systems are emphasized