Bio-Inspired Motion Strategies for a Bimanual Manipulation Task

Steffen JF, Elbrechter C, Haschke R, Ritter H. Bio-Inspired Motion Strategies for a Bimanual Manipulation Task. In: International Conference on Humanoid Robots (Humanoids). 2010

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

Bio-Artificial Synergies for Grasp Posture Control of Supernumerary Robotic Fingers

A new type of wrist-mounted robot, the Supernumerary Robotic (SR) Fingers, is proposed to work closely with the human hand and aid the human in performing a variety of prehensile tasks. For people with diminished functionality of their hands, these robotic fingers could provide the opportunity to live with more independence and work more productively. A natural and implicit coordination between the SR Fingers and the human fingers is required so the robot can be transformed to act as part of the human body. This paper presents a novel control algorithm, termed “Bio-Artificial Synergies”, which enables the SR and human fingers to share the task load together and adapt to diverse task conditions. Through grasp experiments and data analysis, postural synergies were found for a seven-fingered hand comprised of two SR Fingers and five human fingers. The synergy-based control law was then extracted from the experimental data using Partial Least Squares (PLS) regression and tested on the SR Finger prototype as a proof of concept

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

Multifingered robot hand compliant manipulation based on vision-based demonstration and adaptive force control

Multifingered hand dexterous manipulation is quite challenging in the domain of robotics. One remaining issue is how to achieve compliant behaviors. In this work, we propose a human-in-the-loop learning-control approach for acquiring compliant grasping and manipulation skills of a multifinger robot hand. This approach takes the depth image of the human hand as input and generates the desired force commands for the robot. The markerless vision-based teleoperation system is used for the task demonstration, and an end-to-end neural network model (i.e., TeachNet) is trained to map the pose of the human hand to the joint angles of the robot hand in real-time. To endow the robot hand with compliant human-like behaviors, an adaptive force control strategy is designed to predict the desired force control commands based on the pose difference between the robot hand and the human hand during the demonstration. The force controller is derived from a computational model of the biomimetic control strategy in human motor learning, which allows adapting the control variables (impedance and feedforward force) online during the execution of the reference joint angles. The simultaneous adaptation of the impedance and feedforward profiles enables the robot to interact with the environment compliantly. Our approach has been verified in both simulation and real-world task scenarios based on a multifingered robot hand, that is, the Shadow Hand, and has shown more reliable performances than the current widely used position control mode for obtaining compliant grasping and manipulation behaviors

A framework for compliant physical interaction : the grasp meets the task

Although the grasp-task interplay in our daily life is unquestionable, very little research has addressed this problem in robotics. In order to fill the gap between the grasp and the task, we adopt the most successful approaches to grasp and task specification, and extend them with additional elements that allow to define a grasp-task link. We propose a global sensor-based framework for the specification and robust control of physical interaction tasks, where the grasp and the task are jointly considered on the basis of the task frame formalism and the knowledge-based approach to grasping. A physical interaction task planner is also presented, based on the new concept of task-oriented hand pre-shapes. The planner focuses on manipulation of articulated parts in home environments, and is able to specify automatically all the elements of a physical interaction task required by the proposed framework. Finally, several applications are described, showing the versatility of the proposed approach, and its suitability for the fast implementation of robust physical interaction tasks in very different robotic systems

Parametric mechanical design and optimisation of the Canterbury Hand.

As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand

Parametric mechanical design and optimisation of the Canterbury Hand.

As part of worldwide research humanoid robots have been developed for household, industrial and exploratory applications. If such robots are to interact with people and human created environments they will require human-like hands. The objective of this thesis was the parametric design and optimisation of a dexterous, and anthropomorphic robotic end effector. Known as the ‘Canterbury Hand’ it has 11 degree of freedoms with four fingers and a thumb. The hand has applications for dexterous teleoperation and object manipulation in industrial, hazardous or uncertain environments such as orbital robotics. The human hand was analysed so that the Canterbury Hand could copy its motions, appearance and grasp types. An analysis of the current literature on experimental prosthetic and robotic hands was also carried out. A disadvantage of many of these hand designs was that they were remotely powered using large, heavy actuator packs. The advantage of the Canterbury Hand is that it has been designed to hold the motors, wires, and circuit boards entirely within itself; although a belt carried battery pack is required. The hand was modelled using a parametric 3D computer aided design (CAD) program. Two different configurations of the hand were created in the model. One configuration, as a dexterous robot hand, used Ø13mm 3 Watt DC motors, while the other used Ø10mm, 0.5 Watt DC motors (although this hand is still slightly too large for a general prosthesis). The parts within the hand were modelled to permit changes to the geometry. This was necessary for the optimisation process. The bearing geometry of the finger and thumb linkages, as well as the thumb rotation axis was optimised for anthropomorphic motion, appearance and increased force output. A design table within a spreadsheet was created to interact with the CAD models of the hand to quickly implement the optimised geometry. The work reported in this thesis has shown the possibilities for parametric design and optimisation of an anthropomorphic, dexterous robotic hand