Kinect with ROS, interact with oculus: towards dynamic user interfaces for robotic teleoperation

Teleoperation remains an important aspect for robotic systems especially when deployed in unstructured environments. While a range of research strives for robots that are completely autonomous, many robotic applications still require some level of human-in-The-loop control. In any situation where teleoperation is required an effective User Interface (UI) remains a key component within the systems design. Current advancements in Virtual Reality (VR) software and hardware such as the Oculus Rift, HTC Vive and Google Cardboard combined with greater transparency to robotic systems afforded by middleware such as the Robot Operating System (ROS) provides an opportunity to rapidly improve traditional teleoperation interfaces. This paper uses a System of System (SoS) approach to present the concept of a Virtual Reality Dynamic User Interface (VRDUI) for the teleoperation of heterogeneous robots. Different geometric virtual workspaces are discussed and a cylindrical workspace aligned with interactive displays is presented as a virtual control room. A presentation mode within the proposed VRDUI is also detailed, this shows how point cloud information obtained from the Microsoft Kinect can be incorporated within the proposed virtual workspace. This point cloud data is successfully processed into an OctoMap utilizing the octree data structure to create a voxelized representation of the 3D scanned environment. The resulting OctoMap is then displayed to an operator as a 3D point cloud using the Oculus Rift Head Mounted Display (HMD).

Efficacy comparison of clustering systems for limb detection

This paper presents a comparison of applying different clustering algorithms on a point cloud constructed from the depth maps captured by a RGBD camera such as Microsoft Kinect. The depth sensor is capable of returning images, where each pixel represents the distance to its corresponding point not the RGB data. This is considered as the real novelty of the RGBD camera in computer vision compared to the common video-based and stereo-based products. Depth sensors captures depth data without using markers, 2D to 3D-transition or determining feature points. The captured depth map then cluster the 3D depth points into different clusters to determine the different limbs of the human-body. The 3D points clustering is achieved by different clustering techniques. Our Experiments show good performance and results in using clustering to determine different human-body limbs.

Enabling cloud computing in emergency management systems

Emergencies, including both natural and man - made disasters, increasingly pose an immediate threat to life, health, property, and environment. For example, Hurricane Katrina, the deadliest and most destructive Atlantic tropical cyclone of the 2005 Atlantic hurricane season, led to at least 1,883 people's death and an estimated loss of - 108 billion property. To reduce the damage by emergencies, a wide range of cutting-edge technologies on medicine and information are used in all phases of emergency management. This article proposes a cloud-based emergency management system for environmental and structural monitoring that utilizes the powerful computing and storage capability of datacenters to analyze the mass data collected by the wireless intelligent sensor network deployed in civil environment. The system also benefits from smartphone and social network platform to setup the spatial and population models, which enables faster evacuation and better resource allocation.

A low-cost 3-D laser imaging system

This paper presents the design and development of a low cost three-dimensional laser imaging system for scanning suitable surfaces. A generic, low cost, off-the-shelf laser range finder is used to obtain the primary one dimensional distance measurement. The range finder’s laser beam is reflected by a twin-axis mirror assembly driven by stepper motors providing the system with two angular degrees of freedom, allowing 3-D measurements to be determined. A camera and image processing techniques are used to determine the measured 1-D range value from the generic range-finding device. A computer program then uses the obtained data to create a 3-D point cloud. An algorithm is then used to construct a 3-D wire frame mesh representing the scanned surface. The system has an angular resolution of 1.8° and the results obtained demonstrate the system to have an accuracy of approximately ± 2cm at a scanning distance of 1.0m.

Cloud-point extraction of phenanthrene by nonionic surfactants

Extraction and preconcentration of the model polycyclic aromatic hydrocarbon (PAH), phenanthrene, in aqueous solutions by two different kinds of nonionic ethoxylated alcohols, Tergitol 15-S-7 and Neodol 25-7, as extractants was studied at ambient temperature (22°C). Both surfactants have almost the same numbers of hydrocarbons and ethylene-oxide (EO) units, but differ in the location of the alcohols. Neodol 25-7 is a primary alcohol, while Tergitol 15-S-7 is a secondary one. The extraction process is based on the clouding phenomena of these two nonionic surfactants. Addition of sodium sulfate or sodium phosphate could decrease the cloud point temperatures of the surfactant solutions below the ambient temperatures, so that the cloud-point extraction process could be facilitated. Increasing the salt concentration or decreasing the surfactant concentration could improve the preconcentration factor, which is attributable to the decrease in the volume of surfactant-rich phase. Consequently, the recovery efficiency higher than 96% was achieved for phenanthrene in aqueous solution.

A novel cloud-point extraction process for preconcentrating selected polycyclic aromatic hydrocarbons in aqueous solution

A novel but simple cloud-point extraction (CPE) process is developed to preconcentrate the trace of selected polycyclic aromatic hydrocarbons (PAHs) with the use of the readily biodegradable nonionic surfactant Tergitol 15-S-7 as extractant. The concentrations of PAHs, mixtures of naphthalene and phenanthrene as well as pyrene, in the spiked samples were determined with the new CPE process at ambient temperature (23 °C) followed by high performance liquid chromatography (HPLC) with fluorescence detection. More than 80% of phenanthrene and pyrene, respectively, and 96% of naphthalene initially present in the aqueous solutions with concentrations near or below their aqueous solubilities were recovered using this new CPE process. Importantly Tergitol 15-S-7 does not give any fluorometric signal to interfere with fluorescence detection of PAHs in the UV range. No special washing step is, thus, required to remove surfactant before HPLC analyses. Different experimental conditions were studied. The optimum conditions for the preconcentration and determi nation of these selected PAHs at ambient temperature have been established as the following:  (1) 3 wt % surfactant; (2) addition of 0.5 M Na2SO4; (3) 10 min for equilibration time; and (4) 3000 rpm for centrifugal speed with duration of 10 min.

Extending haptic device capability for 3D virtual grasping

This paper presents an investigation into the workspace constraints observed through the use of multiple single point haptic interfaces, which lead to the design of a novel grasping device that improves upon current commercial haptic interfaces. The presented device is desktop based, and has been designed to maximise the haptic workspace while offering the ability to grasp and manipulate virtual objects, which is a function that current commercial interfaces are limited in providing. The performance of the commercial haptic interface in producing sustained effective operation and increased workspace with the attached haptic gripper is evaluated, and the improvement of both has been determined.

Concept design of a novel tactile probe tip for down scaled 3D CMMs

Although coordinate metrology has reached a very high state of development concerning versatility and accuracy for common engineering parts, a high precision capability with nano scale resolution and accuracy is often hard to achieve when it is required to measure very small parts and features. The limiting component is the bulky probing system of traditional CMMs (coordinate measuring machines). In order to satisfy increasing demand for highly accurate geometrical measurements on small parts and small structures, a new measuring probe of high sensitivity and small geometrical dimension with low contact forces needs to be developed. In this paper, a novel probing system, which combines a FBG (Fibre Bragg Grating) embedded optical fibre tactile probe with an optical sensing technique, has been proposed. With the sensor elements integrated into the probe tip directly, the system sensitivity can be increased significantly. A preliminary theoretical analysis of the sensitivity of the FBG fibre sensor under axial and lateral end point loading has been presented and the results show that this micro scale probe has great potential to realize a resolution of 1nanometer on geometrical measurement of small parts.

Sharable file searching in unstructured peer-to-peer systems

The existing sharable file searching methods have at least one of the following disadvantages: (1) they are applicable only to certain topology patterns, (2) suffer single point failure, or (3) incur prohibitive maintenance cost. These drawbacks prevent their effective application in unstructured Peer-to-peer (P2P) systems (where the system topologies are changed time to time due to peers' frequently entering and leaving the systems), despite the considerable success of sharing file search in conventional peer-to-peer systems. Motivated by this, we develop several fully dynamic algorithms for searching sharing files in unstructured peer to peer systems. Our solutions can handle any topology pattern with small search time and computational overhead. We also present an in-depth analysis that provides valuable insight into the characteristics of alternative effective search strategies and leads to precision guarantees. Extensive experiments validate our theoretical findings and demonstrate the efficiency of our techniques in practice.

Effects of additives on the cloud points of selected nonionic linear ethoxylated alcohol surfactants

Effects of various additives including inorganic salts, nonionic and ionic surfactants, water-soluble polymers and alcohols on the cloud points of three linear nonionic surfactants, Tergitol 15-S-7, Tergitol 15-S-9 and Neodol 25-7, were investigated. These surfactants are readily biodegradable and either linear primary or secondary ethoxylated alcohols. Cloud points of these surfactants were functions of their concentrations and concentrations of additives. The cloud points of nonionic surfactant mixtures lay in between the cloud points of individual component surfactants. Presence of two ionic surfactants, sodium dodecyl sulfate (SDS) and cetyl trimethyl ammonium bromide (CTAB), increased the cloud point of 1 wt% Tergitol 15-S-7 micellar solution dramatically when concentrations of ionic surfactants approaching their critical micelle concentration. Addition of water-soluble polymers decreased the cloud point, while addition of inorganic salts can either increase or decrease the cloud points. However, the effect of an alcohol additive on cloud point was dependent on its chain length or its water solubility. Interestingly, synergistic effects between sulfate or phosphate and pentanol on depression of cloud points of Tergitol 15-S-9 were discovered. A linear model predicting cloud points of Tergitol 15-S-X (X = 7, 9 and 12) surfactants and Neodol 25-X (X = 7, 9 and 12) surfactants were proposed with a correlation to logarithm of their ethylene oxide numbers.

Enabling multi-point haptic grasping in virtual environments

Haptic interaction has received increasing research interest in recent years. Currently, most commercially available haptic devices provide the user with a single point of interaction. Multi-point haptic devices present a logical progression in device design and enable the operator to experience a far wider range of haptic interactions, particularly the ability to grasp via multiple fingers. This is highly desirable for various haptically enabled applications including virtual training, telesurgery and telemanipulation. This paper presents a gripper attachment which utilises two low-cost commercially available haptic devices to facilitate multi-point haptic grasping. It provides the ability to render forces to the user's fingers independently and using Phantom Omni haptic devices offers several benefits over more complex approaches such as low-cost, reliability, and ease of programming. The workspace of the gripper attachment is considered and in order to haptically render the desired forces to the user's fingers, kinematic analysis is discussed and necessary formulations presented. The integrated multi-point haptic platform is presented and exploration of a virtual environment using CHAI 3D is demonstrated.

Grasping virtual objects with multi-point haptics

The majority of commercially available haptic devices offer a single point of haptic interaction. These devices are limited when it is desirable to grasp with multiple fingers in applications including virtual training, telesurgery and telemanipulation. Multipoint haptic devices serve to facilitate a greater range of interactions. This paper presents a gripper attachment to enable multi-point haptic grasping in virtual environments. The approach employs two Phantom Omni haptic devices to independently render forces to the user's thumb and other fingers. Compared with more complex approaches to multi-point haptics, this approach provides a number of advantages including low-cost, reliability and ease of programming. The ability of the integrated multi-point haptic platform to interact within a CHAI 3D virtual environment is also presented.

Human action recognition based on 3D SIFT and LDA model

How to recognize human action from videos captured by modern cameras efficiently and effectively is a challenge in real applications. Traditional methods which need professional analysts are facing a bottleneck because of their shortcomings. To cope with the disadvantage, methods based on computer vision techniques, without or with only a few human interventions, have been proposed to analyse human actions in videos automatically. This paper provides a method combining the three dimensional Scale Invariant Feature Transform (SIFT) detector and the Latent Dirichlet Allocation (LDA) model for human motion analysis. To represent videos effectively and robustly, we extract the 3D SIFT descriptor around each interest point, which is sampled densely from 3D Space-time video volumes. After obtaining the representation of each video frame, the LDA model is adopted to discover the underlying structure-the categorization of human actions in the collection of videos. Public available standard datasets are used to test our method. The concluding part discusses the research challenges and future directions.