Impact of end effector technology on telemanipulation performance

Generic requirements for end effector design are briefly summarized as derived from generic functional and operational requirements. Included is a brief summary of terms and definitions related to end effector technology. The second part contains a brief overview of end effector technology work as JPL during the past ten years, with emphasis on the evolution of new mechanical, sensing and control capabilities of end effectors. The third and major part is devoted to the description of current end effector technology. The ongoing work addresses mechanical, sensing and control details with emphasis on mechanical ruggedness, increased resolution in sensing, and close electronic and control integration with overall telemanipulator control system

Development of a Novel Impedance-Controlled Quasi-Direct-Drive Robot Hand

Most robotic hands and grippers rely on actuators with large gearboxes and force sensors for controlling gripping force. However, this might not be ideal for tasks which require the robot to interact with an unstructured and/or unknown environment. We propose a novel quasi-direct-drive two-fingered robotic hand with variable impedance control in the joint space and Cartesian space. The hand has a total of four degrees of freedom, a backdrivable gear train, and four brushless direct current (BLDC) motors. Field-Oriented Control (FOC) with current sensing is used to control motor torques. Variable impedance control allows the hand to perform dexterous manipulation tasks while being safe during human-robot interaction. The quasi-direct-drive actuators enable the fingers to handle contact with the environment without the need for complicated tactile or force sensors. A majority 3D printed assembly makes this a low-cost research platform built with affordable off-the-shelf components. The hand demonstrates grasping with force-closure and form-closure, stable grasps in response to disturbances, tasks exploiting contact with the environment, simple in-hand manipulation, and a light touch for handling fragile objects.Comment: 75 pages, A Thesis in Partial Fulfillment of the Requirements for the Degree of Master of Science in Mechanical Engineering at Stony Brook Universit

Automatic end tool alignment through plane detection with a RANSAC-algorithm for robotic grasping

Camera based grasping algorithms enable the handling of unknown objects without a complete CAD model. In some scenarios, the captured information from a single view is not sufficient or no grasp is possible. For these cases, the precise realignment of the gripper is difficult because a suitable rotation is part of an infinite solution space. In this paper, we propose a framework which automatically identifies correct rotations from point clouds to adjust the gripper. We validate our approach in a virtual environment for a parallel jaw gripper with multiple isolated and grouped industrial objects

Hands: Human to Robotic

Hands have for centuries been recognized as a fundamental tool for humans to gain an understanding of their environment and at the same time be able to manipulate it. In this presentation we will look at various studies made on the functionality and use of the human hand and examine the different approaches to analyzing and classifying human grasps and building a taxonomy of these grasps. We study the anatomy of the human hand, and examine experiments performed to understand the how gripping forces are applied when lifting objects, and the methods extraction of haptic information, by humans. We discuss issues involved in the building of electro-mechanical manipulators and some of the mathematics used in analyzing the suitability of a design. We look at one of the earliest designs of a computer controlled articulated gripper, as well as two of the most prevalent designs in today\u27s research world, the Stanford/JPL hand and the Utah/MIT had. Finally, we show why a more fundamental understanding of how human grasping works will help us design more useful manipulators

Development of an expert system for supporting the selection of robot grippers

The aim of this thesis is to lay the basis for the development of an expert system for the selection of robot grippers. This work has started with a review of the literature of the grasping principles, of releasing strategies and of the main problems concerning the automatic assembly or, more in general, the handling. Later, we have studied a set of parameters constituting the input of the expert system, together with a set of rules aimed at choosing the appropriate gripper. The work ends with a series of tests, with a focus on the food industry, reporting the results and discussing the possibility of future developments