Real-time implementation of an assistive human-machine interface system based around tongue-movement ear pressure (TMEP) signals is presented, alongside results from a series of simulated control tasks. The implementa...
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Real-time implementation of an assistive human-machine interface system based around tongue-movement ear pressure (TMEP) signals is presented, alongside results from a series of simulated control tasks. The implementation of this system into an online setting involves short-term energy calculation, detection, segmentation and subsequent signal classification, all of which had to be reformulated based on previous off-line testing. This has included the formulation of a new classification and feature extraction method. This scheme utilises the discrete cosine transform to extract the frequency features from the time domain information, a univariate Gaussian maximum likelihood classifier and a two phase cross-validation procedure for feature selection and extraction. The performance of this classifier is presented alongside a real-time implementation of the decision fusion classification algorithm, with each achieving 96.28% and 93.12% respectively. The system testing takes into consideration potential segmentation of false positive signals. A simulation mapping commands to a planar wheelchair demonstrates the capacity of the system for assistive robotic control. These are the first real-time results published for a tongue-based human-machine interface that does not require a transducer to be placed within the vicinity of the oral cavity.
This paper describes a fully autonomous mobile urban robot-X1, which can perform multiple tasks autonomously in an unknown urban environment without human guidance, including mobile reconnaissance, target searching, a...
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This paper describes a fully autonomous mobile urban robot-X1, which can perform multiple tasks autonomously in an unknown urban environment without human guidance, including mobile reconnaissance, target searching, and object manipulation. The mission-oriented design, which allows reliability and extensibility of the robotic system, includes a high degree of modularity for both hardware and software architecture, and coordination between tasks. Our strategy specifically addresses fundamental issues such as autonomous navigation in unknown urban environments and vision-based object manipulation. All the functionalities have been proved effective in the real urban environments. The robot platform is being built to provide valuable experiences on autonomous robotics research.
A bipartite state, which is secretly chosen from a finite set of known entangled pure states, cannot immediately be useful in standard quantum information processing tasks. To effectively make use of the entanglement ...
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A bipartite state, which is secretly chosen from a finite set of known entangled pure states, cannot immediately be useful in standard quantum information processing tasks. To effectively make use of the entanglement contained in this unknown state, we introduce a way to locally manipulate the original quantum system: either identify the state successfully or distill some pure entanglement. Remarkably, if many copies are available, we show that any finite set of entangled pure states, whether orthogonal or not, can be locally distinguished in this way, which further implies that pure entanglement can be deterministically extracted from unknown entanglement. These results make it clear why a large class of entangled bipartite quantum operations including unitary operations and measurements that are globally distinguishable can also be locally distinguishable: They can generate pure entanglement consistently.
In this paper we present a method for automatically generating optimal robot trajectories satisfying high level mission specifications. The motion of the robot in the environment is modeled as a weighted transition sy...
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In this paper we present a method for automatically generating optimal robot trajectories satisfying high level mission specifications. The motion of the robot in the environment is modeled as a weighted transition system. The mission is specified by a general linear temporal logic formula. In addition, we require that an optimizing proposition must be repeatedly satisfied. The cost function that we seek to minimize is the maximum time between satisfying instances of the optimizing proposition. For every environment model, and for every formula, our method computes a robot trajectory which minimizes the cost function. The problem is motivated by robotic monitoring and data gathering. In this setting, the optimizing proposition is satisfied at locations where data can be uploaded, and the formula specifies a an infinite horizon data collection mission. Our method utilizes Büchi automata to produce an automaton (which can be thought of as a graph) whose runs satisfy the temporal logic formula. We then present a graph algorithm which computes a path corresponding to the optimal robot trajectory. We also present an implementation for a robot performing a data gathering mission.
The paper proposes a new approach to fuzzy abduction by extending the contraposition rule of propositional logic. The main difficulty of fuzzy abduction is due to the restriction of single antecedent clause in a fuzzy...
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The paper proposes a new approach to fuzzy abduction by extending the contraposition rule of propositional logic. The main difficulty of fuzzy abduction is due to the restriction of single antecedent clause in a fuzzy production rule. When more than one antecedent clause occurs jointly in a fuzzy rule, the membership value of the derived antecedent clauses become equal, which should not be the case in general. The paper overcomes this problem and demonstrates a simple but elegant method to compute premises in a multi-chained reasoning system.
A difference between the human and robots from the viewpoint of motor control is a sampling time in everyday movements. That is, the sampling time for controlling conventional robot systems is required to become appro...
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A difference between the human and robots from the viewpoint of motor control is a sampling time in everyday movements. That is, the sampling time for controlling conventional robot systems is required to become approximately 1 ms. On the other hand, the motor control based on human nervous system permits considerably large time-delay due to the transmission latency on afferent/efferent pathways of the central nervous system. To date, it has been difficult for the robot to acquire dexterous tasks and precise movements as long as the robot system has an unexpected large delay in terms of sensory informations. Based on the above observation, this paper provides a new control strategy to accomplish precise orientation control of a target object grasped by a robotic hand consisting of two degrees-of-freedom (DOFs). The controller, named as serial two-phased (STP) controller, proposed in this study can realize secure grasping and manipulation in the case that a large visual feedback delay induced by the low specification of a camera is hiding in the control loop. Finally, through several simulations, we indicate that the closed loop dynamics designed by integrating the STP controller and a soft-fingertip structure is robust even in at most 100 ms-delay relating to the updating of camera images.
The paper presents the analysis of the subject-specificity of the radio channel in wireless body area networks using a simulation tool based on the parallel finite-difference time-domain technique. This technique is w...
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The paper presents the analysis of the subject-specificity of the radio channel in wireless body area networks using a simulation tool based on the parallel finite-difference time-domain technique. This technique is well suited to model the radio propagation around irregularly shaped, inhomogeneous objects such as the human body. The impact of different digital phantoms on the on-body radio channel was analysed at 2.4 GHz. The analysis demonstrated that the characteristics of the on-body radio channel are subject-specific and are associated with human genders, height, and body mass index.
Radio frequency identification (RFID) is a kind of electronic identification technology that is becoming widely deployed. Compared to traditional RFID system, tags in the proposed smart RFID system would store not onl...
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Radio frequency identification (RFID) is a kind of electronic identification technology that is becoming widely deployed. Compared to traditional RFID system, tags in the proposed smart RFID system would store not only the fixed ID information but also some information which is “active” and encoded in the form of mobile codes indicating the up-to-date situation and associated services' directives. In the proposed system, the service that the RFID tag bearer needs can be explained in a context-aware decision making system to provide a situation-aware system response and offer a good quality of service (QoS).
Ultra wide-band (UWB) is an appealing technology for wireless body area networks (WBANs). The paper presents the numerical analysis of the subject-specificity of the radio channel in UWB-WBANs adopting the finite diff...
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Ultra wide-band (UWB) is an appealing technology for wireless body area networks (WBANs). The paper presents the numerical analysis of the subject-specificity of the radio channel in UWB-WBANs adopting the finite difference time domain technique. The analysis has been performed in the frequency range 3-10 GHz considering nine homogeneous digital phantoms of different size and gender. A two-pole Debye model was used to model the frequency dispersion of the human body muscle tissues, and the results demonstrate that the received power in on-body links is subject-specific and associated with the body mass index of the subject.
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