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The paper addresses path planning for a redundant robot arm that is maneuvering in confined spaces, where neither an explicit model nor external perception of the possibly frequently changing environment is available. Our approach is rather solely based on data from kinesthetic demonstrations of feasible configurations provided by a user. The key challenge is to create a graph-based representation...
It is undeniable that the ability to grasp and handle an object is vital for service robots. From object recognition to object grasping motion, the motion execution should be as fast as possible. Due to the possible position variation of the target object to be grasped, online planning of grasping motion should be done. In order to achieve flexible grasping motion, recurrent neural network could be...
A low-cost and easy-to-customize Cable-driven Wrist Robotic Rehabilitor (CDWRR) has been developed for forearm and wrist motion training. This device can be potentially applied to rehabilitation of stroke patients for three degree-of-freedom (3-DOF) arm motion, including forearm supination/pronation, wrist flexion/extension and ulnar/radial deviation. The CDWRR can be customized for patients with...
Restricted Boltzmann machines (RBMs) and their variants have attracted a lot of attention recently. They have been applied widely, e.g., In handwriting recognition, document categorization and object recognition. Unfortunately, an RBM requires a large parameter space since it is a fully-connected bipartite graph, especially with high dimensional input spaces. Moreover, it is still unclear how it selects...
Between the growth of Internet or World Wide Web (WWW) and the emersion of the social networking site like Friendster, Myspace etc., information society started facing exhilarating challenges in language technology applications such as Machine Translation (MT) and Information Retrieval (IR). Nevertheless, there were researchers working in Machine Translation that deal with real time information for...
As the product of enterprise human resource development in market economy, “order-oriented” talent cultivation mode is a cultivation mode of certain effects and practice accumulation in modern talent cultivation by taking the educational idea of “industry-academy combination” which has achieved certain success. In this paper, the innovative “order-oriented” talent cultivation mode is used for cultivating...
Chinese calligraphy is a unique form of art in the world, whose aesthetic is mainly created by the proper manipulation of the brush. However, it is impossible for a person to figure out the 6-D motion of the brush from calligraphy images, if he has no experience of writing calligraphy. In this paper, we propose a Learning from Demonstration approach for our calligraphy robot, Callibot, to acquire...
We propose a new unsupervised method to identify Named Entities (NE) in resource-poor languages. The idea is to transfer the knowledge of NEs from a resource-rich language to a resource-poor one by using a bilingual parallel corpus of this language pair. After extracting all NE pair candidates and filtering these candidates (includes lexical and contextual filters) to obtain a high precision seed...
Evidence supports the combination of electrical stimulation (ES) and task specific training in rehabilitation of the upper extremity following stroke. The aim of this study is to develop a rehabilitation system that delivers precisely controlled levels of stimulation to the shoulder, elbow and wrist during goal-oriented activity utilising everyday real objects. Iterative learning control (ILC) is...
Surface Electromyography (EMG) is popularly used to decode human motion intention for robot movement control. Traditional motion decoding method uses pattern recognition to provide binary control command which can only move the robot as predefined limited patterns. In this work, we proposed a motion decoding method which can accurately estimate 3-dimensional (3-D) continuous upper limb motion only...
Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of...
Improving the intuitiveness of the interaction between human and machine is an important issue for powered lower-limb prosthesis control. In this research, we aimed to evaluate the potential of using surface electromyography (EMG) signals measured from transtibial amputees' residual muscles to directly control the position of prosthetic ankle. In this research, one transtibial amputee subject and...
This paper describes a novel controller, intended for use in a lower-limb exoskeleton, to aid gait rehabilitation in patients with hemiparesis after stroke. The controller makes use of gravity compensation, feedforward movement assistance, and reinforcement of isometric joint torques to achieve assistance without dictating the spatiotemporal nature of joint movement. The patient is allowed to self-select...
Ankle joint with spasticity and/or contracture can severely affect mobility and independence of stroke survivors. Due to that, the Achilles tendon(AT) is affected. In this paper, we aim to study changes of AT properties via proprioceptive neuromuscular facilitation (PNF) treatment. A robotic ankle-foot rehabilitation system has been proposed, which consists of a robotic ankle-foot platform and a graphic...
Microfluidic diagnostics for use in the developing world face a number of unique challenges. Doctors and nurses in developing countries are best suited to addresses these challenges, but they lack the resources and training needed to develop their own microfluidic diagnostics. To address this need, we are developing a system of Multifluidic Evolutionary Components or MECs, “building blocks” that can...
Contemporary physiotherapy and rehabilitation practice uses subjective measures for motion evaluation and requires time-consuming supervision. Algorithms that can accurately segment patient movement would provide valuable data for progress tracking and on-line patient feedback. In this paper, we propose a two-class classifier approach to label each data point in the patient movement data as either...
Human guide robots need to generate a trajectory from human training. The popular work space methods have to calculate the inverse kinematics. While the joint space methods need the dynamic time warping. These destroy the accuracy of the trajectory model. In this paper, we use Lloyd's algorithm to hidden Markov model (HMM). The advantages of the method over the other HMM are the time difference does...
We introduce a constructive, robust, and adaptive OS-ELM (Online Sequential Extreme Machine Learning) that combines learning strategies of Constructive Enhancement OSELM and Robust OS-ELM, and add adaptive capability to receive a new target class requirement during sequential learning and applied in human action recognition. The overall strategy is aimed to deal against parameters tuning and new requirements...
Gesture recognition is an important task in Human-Robot Interaction (HRI) and the research effort towards robust and high-performance recognition algorithms is increasing. In this work, we present a neural network approach for learning an arbitrary number of labeled training gestures to be recognized in real time. The representation of gestures is hand-independent and gestures with both hands are...
Human action recognition based on the depth maps is an important yet challenging task. In this paper, a new framework based on the 3D motion trail model (3DMTM) and Pyramid Histograms of Oriented Gradient (PHOG) is proposed to recognize human actions from sequences of depth maps. Specifically, a discriminative descriptor called 3DMTM-PHOG is proposed for depth-based human action recognition. The 3DMTM...
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