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We consider a network of sensors wherein the state estimates are sent from sensors to a fusion center to generate a global state estimate. The underlying fusion algorithm affects the performance measure QCC(τ) (with subscripts CC indicating the effects of the communications and computing quality) of the global state estimate computed within the allocated time τ. We present a probabilistic performance...
We propose that robot perception is enabled by means of a common sensorimotor semantics arising from a set of symmetry theories (expressed as symmetry detectors and parsers) embedded a priori in each robot. These theories inform the production of structural representations of sensorimotor processes, and these representations, in turn, permit perceptual fusion to broaden categories of activity. Although...
In our daily life, much information related to tactile properties of natural objects can also be perceived by our eyes. This is because our brain has a very sophisticated mechanism permitting to associate the memories obtained from different sensory channels and make them work as a whole. In the present study, given a set of representative textile fabrics, a number of standardized sensory experiments...
Considerable time and effort often go into designing and implementing experimental set-ups (ES) in robotics. These activities are usually not at the focus of our research and thus go underreported. This results in replication of work and lack of comparability. This paper lays out our view of the theoretical considerations necessary when deciding on the type of experiment to conduct. It describes our...
This paper presents a novel distributed binary sensing paradigm for walker recognition based on a well-known geometric probability model: Buffon's needle. The research aims to achieve a low-data-throughput gait biometric system suitable for wireless sensor network applications. We presents two types of Buffon's needle (BN) models for gait recognition: (1) a classical BN model based on a static distribution...
Since the visual system is susceptible to the lighting condition and surroundings changes, the accuracy for object localization of robot grasping system based on visual servo is rather poor so as to the low grasping success rate and bad robustness of the whole system. In view of such phenomenon, in this paper, we propose a method of fusing binocular camera accompany with monocular vision, IR sensors,...
In this work we use hand configuration and contact points during in-hand object exploration to identify the manipulated objects. Different contact points associated to an object shape can be represented in a latent space and lie on a lower dimensional non-linear manifold in the contact points space which is suitable for modelling and recognition. Associating and learning hand configurations to specific...
This paper proposes a novel algorithm for recognizing the shape of object which in contact with a robotic finger through the tactile pressure sensing. The developed algorithm is capable of distinguishing the contact shapes between a set of low-resolution pressure map. Within this algorithm, a novel feature extraction technique is developed which transforms a pressure map into a 512-feature vector...
This paper introduces the design of a 6-DOF force and torque sensor that uses fiber optic guided light and linear polarizer materials to measure the applied force and torque on a grasped object. The sensor is also capable of measuring the contact direction between the sensor and the object. The developed sensor has a diameter of 16 mm, height of 15.75 mm and weight of 1 gram. The sensor's parallel...
Node localization has long been established as a key problem in the sensor networks. Self-mapping in wireless sensor network which enables beacon-based systems to build a node map on-the-fly extends the range of the sensor network's applications. A variety of self-mapping algorithms have been developed for the sensor networks. Some algorithms assume no information and estimate only the relative location...
This paper presents an effective egomotion solution based on high curvature image features described using local intensity histograms for stereo matching and tracking. To robustify the visual processing system, we propose feature extraction over moment image representation to overcome the adverse effects of illumination changes. A bundle adjustment optimisation technique, thoroughly analysed for different...
The mapping of environments is a prerequisite for many navigation and manipulation tasks. We propose a novel method for acquiring 3D maps of indoor scenes from a freely moving RGB-D camera. Our approach integrates color and depth cues seamlessly in a multi-resolution map representation. We consider measurement noise characteristics and exploit dense image neighborhood to rapidly extract maps from...
This paper presents an approach to solve the data association problem for a hybrid metric map representation. The hybrid metric map representation uses Voronoi diagram to partition the global map space into a series of local subregions, and then a local dense map is built in each subregion. Finally the global feature map and the local maps make up of the hybrid metric map, which can represent all...
In this work, we propose a robust and flexible appearance model based on the structured sparse representation framework. In our method, we model the complex nonlinear appearance manifold and occlusions as a sparse linear combination of structured union of subspaces in a basis library consisting of multiple learned low dimensional subspaces and a partitioned occlusion template set. In order to enhance...
This paper presents a distributed, compressive multiple human tracking system based on binary pyroelectric infrared (PIR) sensor networks. The goal of our research is to develop an energy-efficient, low-data-throughput infrared surveillance system for various indoor applications. The compressive measurements are achieved by using techniques of (1) multiplex binary sensing and (2) space encoding. The...
This paper is about an experimental set-up for tracking a ground moving mobile object from a bird's eye view. In this experiment, an RGB and depth camera is used for detecting moving points. The detected points serve as input for a probabilistic extended object tracking algorithm that simultaneously estimates the kinematic parameters and the shape parameters of the object. By this means, it is easy...
This paper presents a method for optimally combining pixel information from an infra-red thermal imaging camera, and a conventional visible spectrum colour camera, for tracking a moving target. The tracking algorithm rapidly re-learns its background models for each camera modality from scratch at every frame. This enables, firstly, automatic adjustment of the relative importance of thermal and visible...
As a nation of an estimated 45 million uninsured and underinsured Americans (almost 15% of the population), out of which over 11 million suffer from chronic diseases who require constant medical supervision, America today is plagued by the national crisis of inadequate and expensive healthcare. This paper introduces an architecture of a multi-tier telemedicine system comprised of strategically placed...
This paper describes a design and simulation device for the aircraft drilling end-effector based on bionics which is mainly for robotic drilling on the aircraft surface and inner structures. The whole system is composed of six modules which are controlled by master-slave architecture. Automation studio programming software provides a programming pattern to control hardware system. Experiments show...
The Timed Up and Go (TUG) is a clinical test used widely to measure balance and mobility, e.g. in Parkinson's disease (PD). The test includes a sequence of functional activities, namely: sit-to-stand, 3-meters walk, 180° turn, walk back, another turn and sit on the chair. Meanwhile the stopwatch is used to score the test by measuring the time which the patients with PD need to perform the test. Here,...
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