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Frontiers in Neurorobotics

Juanjuan Zhang, Steven H Collins
This study uses theory and experiments to investigate the relationship between the passive stiffness of series elastic actuators and torque tracking performance in lower-limb exoskeletons during human walking. Through theoretical analysis with our simplified system model, we found that the optimal passive stiffness matches the slope of the desired torque-angle relationship. We also conjectured that a bandwidth limit resulted in a maximum rate of change in torque error that can be commanded through control input, which is fixed across desired and passive stiffness conditions...
2017: Frontiers in Neurorobotics
Tatsuro Yamada, Shingo Murata, Hiroaki Arie, Tetsuya Ogata
An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents...
2017: Frontiers in Neurorobotics
Marco Iosa, Giovanni Morone, Stefano Paolucci
Human walking is a complex task which includes hundreds of muscles, bones and joints working together to deliver harmonic movements with the need of finding equilibrium between moving forward and maintaining stability. Many different computational approaches have been used to explain human walking mechanisms, from pendular model to fractal approaches. A new perspective can be gained from using the principles developed in the field of Optimization theory and in particularly the branch of Game Theory. In particular we provide a new insight into human walking showing as the trade-off between advancement and equilibrium managed during walking has the same solution of the Ultimatum game, one of the most famous paradigms of game theory, and this solution is the golden ratio...
2017: Frontiers in Neurorobotics
Tomoaki Nakamura, Takayuki Nagai, Daichi Mochihashi, Ichiro Kobayashi, Hideki Asoh, Masahide Kaneko
Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions. People can divide continuous information into segments without using explicit segment points. This capacity for unsupervised segmentation is also useful for robots, because it enables them to flexibly learn languages, gestures, and actions. In this paper, we propose a Gaussian process-hidden semi-Markov model (GP-HSMM) that can divide continuous time series data into segments in an unsupervised manner...
2017: Frontiers in Neurorobotics
Akira Taniguchi, Tadahiro Taniguchi, Angelo Cangelosi
In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot...
2017: Frontiers in Neurorobotics
Faramarz Faghihi, Ahmed A Moustafa
No abstract text is available yet for this article.
2017: Frontiers in Neurorobotics
Quan Liu, Aiming Liu, Wei Meng, Qingsong Ai, Sheng Q Xie
Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint...
2017: Frontiers in Neurorobotics
Paolo Tommasino, Domenico Campolo
A major challenge in robotics and computational neuroscience is relative to the posture/movement problem in presence of kinematic redundancy. We recently addressed this issue using a principled approach which, in conjunction with nonlinear inverse optimization, allowed capturing postural strategies such as Donders' law. In this work, after presenting this general model specifying it as an extension of the Passive Motion Paradigm, we show how, once fitted to capture experimental postural strategies, the model is actually able to also predict movements...
2017: Frontiers in Neurorobotics
Taiping Zeng, Bailu Si
It is a challenge to build robust simultaneous localization and mapping (SLAM) system in dynamical large-scale environments. Inspired by recent findings in the entorhinal-hippocampal neuronal circuits, we propose a cognitive mapping model that includes continuous attractor networks of head-direction cells and conjunctive grid cells to integrate velocity information by conjunctive encodings of space and movement. Visual inputs from the local view cells in the model provide feedback cues to correct drifting errors of the attractors caused by the noisy velocity inputs...
2017: Frontiers in Neurorobotics
Myunghee Kim, Steven H Collins
Below-knee amputation is associated with higher energy expenditure during walking, partially due to difficulty maintaining balance. We previously found that once-per-step push-off work control can reduce balance-related effort, both in simulation and in experiments with human participants. Simulations also suggested that changing ankle inversion/eversion torque on each step, in response to changes in body state, could assist with balance. In this study, we investigated the effects of ankle inversion/eversion torque modulation on balance-related effort among amputees (N = 5) using a multi-actuated ankle-foot prosthesis emulator...
2017: Frontiers in Neurorobotics
Hong Zeng, Yanxin Wang, Changcheng Wu, Aiguo Song, Jia Liu, Peng Ji, Baoguo Xu, Lifeng Zhu, Huijun Li, Pengcheng Wen
Brain-machine interface (BMI) can be used to control the robotic arm to assist paralysis people for performing activities of daily living. However, it is still a complex task for the BMI users to control the process of objects grasping and lifting with the robotic arm. It is hard to achieve high efficiency and accuracy even after extensive trainings. One important reason is lacking of sufficient feedback information for the user to perform the closed-loop control. In this study, we proposed a method of augmented reality (AR) guiding assistance to provide the enhanced visual feedback to the user for a closed-loop control with a hybrid Gaze-BMI, which combines the electroencephalography (EEG) signals based BMI and the eye tracking for an intuitive and effective control of the robotic arm...
2017: Frontiers in Neurorobotics
Usman Ghafoor, Sohee Kim, Keum-Shik Hong
For those individuals with upper-extremity amputation, a daily normal living activity is no longer possible or it requires additional effort and time. With the aim of restoring their sensory and motor functions, theoretical and technological investigations have been carried out in the field of neuroprosthetic systems. For transmission of sensory feedback, several interfacing modalities including indirect (non-invasive), direct-to-peripheral-nerve (invasive), and cortical stimulation have been applied. Peripheral nerve interfaces demonstrate an edge over the cortical interfaces due to the sensitivity in attaining cortical brain signals...
2017: Frontiers in Neurorobotics
Qingpeng Zhu, Jochen Triesch, Bertram E Shi
This paper investigates two types of eye movements: vergence and saccades. Vergence eye movements are responsible for bringing the images of the two eyes into correspondence, whereas saccades drive gaze to interesting regions in the scene. Control of both vergence and saccades develops during early infancy. To date, these two types of eye movements have been studied separately. Here, we propose a computational model of an active vision system that integrates these two types of eye movements. We hypothesize that incorporating a saccade strategy driven by bottom-up attention will benefit the development of vergence control...
2017: Frontiers in Neurorobotics
Kai Schmidt, Jaime E Duarte, Martin Grimmer, Alejandro Sancho-Puchades, Haiqi Wei, Chris S Easthope, Robert Riener
Muscle weakness-which can result from neurological injuries, genetic disorders, or typical aging-can affect a person's mobility and quality of life. For many people with muscle weakness, assistive devices provide the means to regain mobility and independence. These devices range from well-established technology, such as wheelchairs, to newer technologies, such as exoskeletons and exosuits. For assistive devices to be used in everyday life, they must provide assistance across activities of daily living (ADLs) in an unobtrusive manner...
2017: Frontiers in Neurorobotics
Sébastien Mick, Daniel Cattaert, Florent Paclet, Pierre-Yves Oudeyer, Aymar de Rugy
Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude...
2017: Frontiers in Neurorobotics
Jie Zhang, Man Kang, Xiaojuan Li, Geng-Yang Liu
Genetic algorithms are widely adopted to solve optimization problems in robotic applications. In such safety-critical systems, it is vitally important to formally prove the correctness when genetic algorithms are applied. This paper focuses on formal modeling of crossover operations that are one of most important operations in genetic algorithms. Specially, we for the first time formalize crossover operations with higher-order logic based on HOL4 that is easy to be deployed with its user-friendly programing environment...
2017: Frontiers in Neurorobotics
Michael Wininger, Panagiotis Artemiadis, Claudio Castellini, Patrick Pilarski
No abstract text is available yet for this article.
2017: Frontiers in Neurorobotics
Aïsha Sahaï, Elisabeth Pacherie, Ouriel Grynszpan, Bruno Berberian
Nowadays, interactions with others do not only involve human peers but also automated systems. Many studies suggest that the motor predictive systems that are engaged during action execution are also involved during joint actions with peers and during other human generated action observation. Indeed, the comparator model hypothesis suggests that the comparison between a predicted state and an estimated real state enables motor control, and by a similar functioning, understanding and anticipating observed actions...
2017: Frontiers in Neurorobotics
Ruiqi Wu, Changle Zhou, Fei Chao, Zuyuan Zhu, Chih-Min Lin, Longzhi Yang
Inspired by infant development theories, a robotic developmental model combined with game elements is proposed in this paper. This model does not require the definition of specific developmental goals for the robot, but the developmental goals are implied in the goals of a series of game tasks. The games are characterized into a sequence of game modes based on the complexity of the game tasks from simple to complex, and the task complexity is determined by the applications of developmental constraints. Given a current mode, the robot switches to play in a more complicated game mode when it cannot find any new salient stimuli in the current mode...
2017: Frontiers in Neurorobotics
Xu Zhang, Xiangxin Li, Oluwarotimi Williams Samuel, Zhen Huang, Peng Fang, Guanglin Li
Electromyogram (EMG) contains rich information for motion decoding. As one of its major applications, EMG-pattern recognition (PR)-based control of prostheses has been proposed and investigated in the field of rehabilitation robotics for decades. These prostheses can offer a higher level of dexterity compared to the commercially available ones. However, limited progress has been made toward clinical application of EMG-PR-based prostheses, due to their unsatisfactory robustness against various interferences during daily use...
2017: Frontiers in Neurorobotics
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