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Current brain-machine interfaces (BMIs) allow upper limb amputees to position robotic arms with a high degree of accuracy, but lack the ability to control hand pre-shaping for grasping different objects. We have previously shown that low frequency (0.1–1 Hz) time domain cortical activity recorded at the scalp via electroencephalography (EEG) encodes information about grasp pre-shaping. To transfer...
In this paper development, implementation and experimental validation of a grasp synthesis algorithm for an anthropomorphic robotic arm-hand system in a low dimensional posture subspace is proposed. The algorithm has been developed on the basis of the analysis of human hand postural synergies. Drawing inspiration from neuroscientific studies, a database of grasps has been created through the observation...
If grasping force of prosthetic hand is higher than the desired, the grasping object may produce undesired deformation or crash. In order to reduce the phenomenon, a simple control method is proposed to prevent overshoot of grasping force. Based on impedance control, a dynamic interaction force between a tendon-driven prosthetic hand and environment is modeled. A PID controller can be simple designed...
This paper describes an haptic system designed to vary the stiffness of three contact points in an independent and controllable fashion, by suitably regulating the inner pressure of three pneumatic tactile displays. At the same time, the contact forces exerted by the user are measured by six degree-of-freedom force sensors placed under each finger. This device might be profitably used in hand rehabilitation...
Robotic hands can be applied in different applications such as prosthesis, humanoid robots, industrial robotic manipulators and other kinds of robotic arms. Introduction of robotic technology into the field of prosthesis has resulted a higher quality of life for amputees. In this paper an under-actuated mechanism which has the self-adaptation ability is proposed to be used in the fingers of the hand...
A robot hand-over control scheme is proposed achieving human-like haptic interaction during object load transfer from a giver to a receiver hand for the planar case. It is assumed that the object has parallel surfaces and unknown mass. The giver initiates the hand-over process while the receiver estimates the transferred object mass adapting its grip force accordingly in a three stage process. The...
We present a novel approach to the problem of autonomously recognizing and unfolding articles of clothing using a dual manipulator. The problem consists of grasping an article from a random point, recognizing it and then bringing it into an unfolded state. We propose a data-driven method for clothes recognition from depth images using Random Decision Forests. We also propose a method for unfolding...
This work presents scenario oriented Color-Depth integration framework for the purpose of robust object segmentation in a real workplace scenario. The workplace is the Library of Bremen University and the objects to be grasped are books located on a shelf. The proposed framework is responsible for segmenting the book to be grasped and extract the features needed for a successful grasping operation...
The need for combined task and motion planning in robotics is well understood. Solutions to this problem have typically relied on special purpose, integrated implementations of task planning and motion planning algorithms. We propose a new approach that uses off-the-shelf task planners and motion planners and makes no assumptions about their implementation. Doing so enables our approach to directly...
In many complex robot applications, such as grasping and manipulation, it is difficult to program desired task solutions beforehand, as robots are within an uncertain and dynamic environment. In such cases, learning tasks from experience can be a useful alternative. To obtain a sound learning and generalization performance, machine learning, especially, reinforcement learning, usually requires sufficient...
In this paper, we propose an optimization scheme for deriving task-specific force closure grasps for underactuated robot hands. Motivated by recent neuroscientific studies on the human grasping behavior, a novel grasp strategy is built upon past analysis regarding the task-specificity of human grasps, that also complies with the recent soft synergy model of underactuated hands. Our scheme determines...
In this paper we present an automated system that is able to track and grasp a moving object within the workspace of a manipulator using range images acquired with a Microsoft Kinect sensor. Realtime tracking is achieved by a geometric particle filter on the affine group. Based on the tracked output, the pose of a 7-DoF WAM robotic arm is continuously updated using dynamic motor primitives until a...
In this paper, we present a real-time motion and force capturing system for tele-operated robotic manipulation that combines surface-electromyogram (sEMG) pattern recognition with an inertia measurement unit(IMU) for motion calculation. The purpose of this system is to deliver the human motion and intended force to a remote robotic manipulator and to realize multi-fingered activities-of-daily-living...
We present a novel method for classifying and estimating the categories and poses of deformable objects, such as clothing, from a set of depth images. The framework presented here represents the recognition part of the entire pipeline of dexterous manipulation of deformable objects, which contains grasping, recognition, regrasping, placing flat, and folding. We first create an off-line simulation...
There has been a growing enthusiasm to use anthropomorphic hands of humanoid robots to manipulate every-day objects and tools designed for humans. However, multi-fingered grasping imposes a formidable control challenge due to the high dimensionality of the joint space and the difficulty to form a functional grip on objects. We propose a hybrid technique based on grasping synergies extracted from kinaesthetic...
We present a novel method for three-finger precision grasp and its implementation in a complete grasping tool-chain. We start from binocular vision to recover the partial 3D structure of unknown objects. We then process the incomplete 3D point clouds searching for good triplets according to a function that accounts for both the feasibility and the stability of the solution. In particular, while stability...
In this study, we experimentally investigated the effect of robot fingertip stiffness on friction during grasping of an object. To make robots more human-friendly, robotic hands with soft surfaces have been developed. A soft fingertip, i.e., one with low stiffness, is considered desirable because it produces high friction. However, in our experiments, we were able to obtain high friction from a stiff...
Object-level impedance control is of great importance for object-centric tasks, such as robust grasping and dexterous manipulation. Despite the recent progress on this topic, how to specify the desired object impedance for a given task remains an open issue. In this paper, we decompose the object's impedance into two complementary components-the impedance for stable grasping and impedance for object...
Pose estimation of object is one of the key problems for the automatic-grasping task of robotics. In this paper, we present a new vision-based robotic grasping system, which can not only recognize different objects but also estimate their poses by using a deep learning model, finally grasp them and move to a predefined destination. The deep learning model demonstrates strong power in learning hierarchical...
High flexibility and high speed is the goal for industrial manufacturing using robots. However, it is difficult to put them together due to the fact that they are contradicting with each other. To solve this problem, a new high reconfigurable gripper is proposed for robotic manipulator to improve its flexibility, so that the robot can accomplish an assembly task with shorter time. In this paper, the...
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