Team THOR's Entry in the DARPA Robotics Challenge Finals 2015

This paper describes Team THOR's approach to human‐in‐the‐loop disaster response robotics for the 2015 DARPA Robotics Challenge (DRC) Finals. Under the duress of unpredictable networking and terrain, fluid operator interactions and dynamic disturbance rejection become major concerns for effective teleoperation. We present a humanoid robot designed to effectively traverse a disaster environment while allowing for a wide range of manipulation abilities. To complement the robot hardware, a hierarchical software foundation implements network strategies that provide real‐time feedback to an operator under restricted bandwidth using layered user interfaces. Our strategy for humanoid locomotion includes a backward‐facing knee configuration paired with specialized toe and heel lifting strategies that allow the robot to traverse difficult surfaces while rejecting external perturbations. With an upper body planner that encodes operator preferences, predictable motion plans are executed in unforeseen circumstances. These plans are critical for manipulation in unknown environments. Our approach was validated during the DRC Finals competition, where Team THOR scored three points in 18 min of operation time, and the results are presented along with an analysis of each task.     

Real-time approximation of molecular interaction interfaces based on hierarchical space decomposition

The interaction interface between two molecules can be represented as a bisector surface equidistant from the two sets of spheres of varying radii representing atoms. We recursively divide a box containing both sphere-sets into uniform pairs of sub-boxes. The distance from each new box to each sphere-set is conservatively approximated by an interval, and the number of sphere-box computations is greatly reduced by pre-partitioning each sphere-set using a kd-tree. The subdivision terminates at a specified resolution, creating a box partition (BP) tree. A piecewise linear approximation of the bisector surface is then obtained by traversing the leaves of the BP tree and connecting points equidistant from the sphere-sets. In 124 experiments with up to 16,728 spheres, a bisector surface with a resolution of 1/2⁴ of the original bounding box was obtained in 28.8 ms on average.     

Analysis of zero-inflated clustered count data: A marginalized model approach

Min and Agresti (2005) proposed random effect hurdle models for zero-inflated clustered count data with two-part random effects for a binary component and a truncated count component. In this paper, we propose new marginalized models for zero-inflated clustered count data using random effects. The marginalized models are similar to Dobbie and Welsh’s (2001) model in which generalized estimating equations were exploited to find estimates. However, our proposed models are based on a likelihood-based approach. A Quasi-Newton algorithm is developed for estimation. We use these methods to carefully analyze two real datasets.     

Contour matching using epipolar geometry

Matching features computed in images is an important process in multiview image analysis. When the motion between two images is large, the matching problem becomes very difficult. In this paper, we propose a contour matching algorithm based on geometric constraints. With the assumption that the contours are obtained from images taken from a moving camera with static scenes, we apply the epipolar constraint between two sets of contours and compute the corresponding points on the contours. From the initial epipolar constraints obtained from corner point matching, candidate contours are selected according to the epipolar geometry, contour end point constraints, and contour distance measures. In order to reduce the possibility of false matches, the number of match points on a contour is also used as a selection measure. The initial epipolar constraint is refined from the matched sets of contours. The algorithm can be applied to a pair or two pairs of images. All of the processes are fully automatic and successfully implemented and tested with various real images     

An Exploratory Study: Supporting Collaborative Multimedia Systems Design

Multimedia systems design generally requires a collaborative effort from a group of designers with a variety of backgrounds and tasks, such as content experts, instructional designers, media specialists, users, and so forth. However, currently available design tools on the market are mainly designed for a single user. Tools intended to support a collaborative design process should coordinate independent activities of individual designers.This research investigated support for work groups engaged in designing multimedia systems. Specifically, it discussed a new collaborative design environment, called the KMS (Knowledge Management System)-based design environment, in which multimedia designers could share their design knowledge freely. Through two experimental groups, the research investigated impacts of the KMS-based design environment on their collaborative design activities (knowledge creating, knowledge securing, knowledge distributing, and knowledge retrieving activities). The research findings showed that the KMS-based design environment was a promising environment for collaborative multimedia systems design. More specifically, the research findings indicated that the KMS-based design environment supported creating, securing, and retrieving knowledge, but it did not support distributing knowledge. In addition, the research found that the social interactions between group members played important roles in the success of the collaborative multimedia systems design and that the KMS-based design environment did not support the socialization of group members. Furthermore, the research found that the inability of the KMS-based design environment to support the socialization was linked to its low performance level in supporting the knowledge distributing activity. The research explored the desired features of a collaborative support tool for multimedia systems design.     

Numerical assessment of turbulent models at a critical regime on unstructured meshes

The present study mainly aims to investigate the performances of different turbulent models for the flow simulation around a circular cylinder at a critical Reynolds number regime (Re = 8.5×10⁵, Tu = 0.7%). A hybrid RANS/LES model (SAS model), a correlation-based transition model ( $\gamma - \widetilde{\operatorname{Re} }_{\theta t} $ model), and a fully turbulent RANS model (SST model) were used to simulate various flow features, such as laminar-turbulence transition inside the boundary layer and the unsteady vortex shedding in the wake region, and their feasibilities for the flow simulation at a critical Reynolds number regime were demonstrated. A vertex-centered finite-volume method was used to discretize the incompressible Navier-Stokes equations, and an unstructured mesh technique was used to discretize the computational domain. The inviscid fluxes were evaluated using 2^nd-order Roe??s flux difference splitting, and the viscous fluxes were computed based on central differencing. A dual time-stepping method and the Gauss-Seidel iteration were used for unsteady time integration. The parallelization strategy using METIS and MPI libraries was used to reduce computational costs. The unsteady characteristics and the time-averaged quantities of the flow fields were compared between turbulent models. The numerical results were also compared with experimental results. The turbulent models showed quite different results at the critical regime because of the different abilities of each model to predict various flow features, such as laminar-turbulence transition and unsteady vortex shedding.     

Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting

This study considers real estate appraisal forecasting problem. While there is a great deal of literature about use of artificial intelligence and multiple linear regression for the problem, there has been always controversy about which one performs better. Noting that this controversy is due to difficulty finding proper predictor variables in real estate appraisal, we propose a modified version of ridge regression, i.e., ridge regression coupled with genetic algorithm (GA-Ridge). In order to examine the performance of the proposed method, experimental study is done for Korean real estate market, which verifies that GA-Ridge is effective in forecasting real estate appraisal. This study addresses two critical issues regarding the use of ridge regression, i.e., when to use it and how to improve it.     

The preparation of carbon nanotubes by dc arc discharge using a carbon cathode coated with catalyst

Carbon nanotubes (CNTs) were grown using a dc arc discharge process and relevant process parameters were investigated. Unlike the usual process in which a carbon anode is filled with metal catalyst powder, CNTs were prepared using a carbon cathode on which the metal catalyst had been deposited using an electroplating system. Various transition metals were investigated. The results show that multi walled carbon nanotubes (MWNTs) and single walled carbon nanotubes (SWNTs) can both be synthesized using this technique. SWNTs are detected in the soot sample collected around the cathode, whereas the MWNTs are detected mainly in the deposit sample collected from the central area of the cathode. The CNT yield varies depending on the catalyst used and the properties of a good catalyst are discussed.     

A method for evaluating fault coverage using simulated fault injection for digitalized systems in nuclear power plants

The fault coverage for digital system in nuclear power plants is evaluated using a simulated fault injection method. Digital systems have numerous advantages, such as hardware elements share and hardware replication of the needed number of independent channels. However, the application of digital systems to safety-critical systems in nuclear power plants has been limited due to reliability concerns. In the reliability issues, fault coverage is one of the most important factors. In this study, we propose an evaluation method of the fault coverage for safety-critical digital systems in nuclear power plants. The system under assessment is a local coincidence logic processor for a digital plant protection system at Ulchin nuclear power plant units 5 and 6. The assessed system is simplified and then a simulated fault injection method is applied to evaluate the fault coverage of two fault detection mechanisms. From the simulated fault injection experiment, the fault detection coverage of the watchdog timer is 44.2% and that of the read only memory (ROM) checksum is 50.5%. Our experiments show that the fault coverage of a safety-critical digital system is effectively quantified using the simulated fault injection method.