An Algorithm for Task Allocation and Planning for a Heterogeneous Multi-Robot System to Minimize the Last Task Completion Time

This paper proposes an algorithm that provides operational strategies for multiple heterogeneous mobile robot systems utilized in many real-world applications, such as deliveries, surveillance, search and rescue, monitoring, and transportation. Specifically, the authors focus on developing an algorithm that solves a min-max multiple depot heterogeneous asymmetric traveling salesperson problem (MDHATSP). The algorithm is designed based on a primal-dual technique to operate given multiple heterogeneous robots located at distinctive depots by finding a tour for each robot such that all the given targets are visited by at least one robot while minimizing the last task completion time. Building on existing work, the newly developed algorithm can solve more generalized problems, including asymmetric cost problems with a min-max objective. Though producing optimal solutions requires high computational loads, the authors aim to find reasonable sub-optimal solutions within a short computation time. The algorithm was repeatedly tested in a simulation with varying problem sizes to verify its effectiveness. The computational results show that the algorithm can produce reliable solutions to apply in real-time operations within a reasonable time

Endometrioid Adenocarcinoma in Urethrovaginal Septum: A Diagnostic Pitfall

Primary endometrioid adenocarcinoma developed at urethrovaginal septum has not been reported. A 61-yr-old woman presented with recurrent urinary tract infection. She had received hormone replacement treatment with estrogen and progesterone for 5 yr. A pinpoint ulceration at slightly elevated anterior vaginal wall was found and biopsy revealed endometrioid adenocarcinoma. Magnetic resonance imaging showed the 4.3 cm sized mass in urethrovaginal septum. She has undergone anterior pelvic exenteration, pelvic lymph node dissection, and urostomy with ileal conduit. Microscopic finding of the pathology revealed endometrioid adenocarcinoma. Co-existence of endometriosis was not identified. Tumor at urethrovaginal septum was difficult to be detected till growing to be bulky, because of vaginal axis, misunderstanding of the tumor as symphysis pubis, no definitive symptom, and its rarity. This is the first reported case of extraovarian endometrioid adenocarcinoma developed at the urethrovaginal septum. Understanding normal functional anatomy and meticulous physical examination are essential to detect this rare tumor in the urethrovaginal septum

A Heuristic for Efficient Coordination of Multiple Heterogeneous Mobile Robots Considering Workload Balance

The letter deals with a path planning problem that commonly arises in many applications involving multiple heterogeneous robots called a Multiple Depot Heterogeneous Traveling Salesman Problem (MDHTSP). Specifically, the authors seek to provide good quality of feasible solutions for a path planning problem for a given set of structurally heterogeneous mobile robots located in distinctive depots and a set of targets to visit while minimizing the maximum travel cost (min-max). A solution for MDHTSP with min-max objectives is in great demand for many applications, such as transportation and surveillance, because it is directly related to a significant reduction in the mission completion time. However, no reliable algorithm running in a reasonable computation time has been published for this specific problem. As an extension of our preliminary research on two heterogeneous robots, this letter presents a heuristic approach based on a primal-dual technique for the problem while focusing on the target assignment. The computational results of the implementation verify that the proposed algorithm produces a good quality of feasible solution within a relatively short computation time

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This article reports on the design, analysis and control of a new type of wheeled mobile robot based on a nonholonomic spherical continuously variable transmission (S-CVT). Our S-CVT based mobile robot is designed to increase the run time (i.e., the length of time in which the robot can be operated), and to achieve full planar accessibility with the design of a novel pivoting device that takes advantage of the flexibility of the S-CVT. We examine the sources of power loss in the S-CVT, in particular spin loss. For a quantitative analysis of spin loss of the S-CVT, we develop a friction model for the S-CVT, and perform an in-depth contact analysis based on the relative velocity field and normal pressure distribution. We also present a nonlinear shifting controller based on feedback linearization that takes into account the dynamics of the S-CVT. To evaluate the energy efficiency of our mobile robot and the performance of the S-CVT a

An Efficient Framework for Development of Task-Oriented Dialog Systems in a Smart Home Environment

In recent times, with the increasing interest in conversational agents for smart homes, task-oriented dialog systems are being actively researched. However, most of these studies are focused on the individual modules of such a system, and there is an evident lack of research on a dialog framework that can integrate and manage the entire dialog system. Therefore, in this study, we propose a framework that enables the user to effectively develop an intelligent dialog system. The proposed framework ontologically expresses the knowledge required for the task-oriented dialog system’s process and can build a dialog system by editing the dialog knowledge. In addition, the framework provides a module router that can indirectly run externally developed modules. Further, it enables a more intelligent conversation by providing a hierarchical argument structure (HAS) to manage the various argument representations included in natural language sentences. To verify the practicality of the framework, an experiment was conducted in which developers without any previous experience in developing a dialog system developed task-oriented dialog systems using the proposed framework. The experimental results show that even beginner dialog system developers can develop a high-level task-oriented dialog system

Automatic text categorization using the importance of sentences

Automatic text categorization is a problem of assigning text documents to pre-defined categories. In order to classify text documents, we must extract useful features. In previous researches, a text document is commonly represented by the term frequency and the inverted document frequency of each feature. Since there is a difference between important sentences and unimportant sentences in a document, the features from more important sentences should be considered more than other features. In this paper, we measure the importance of sentences using text summarization techniques. Then we represent a document as a vector of features with different weights according to the importance of each sentence. To verify our new method, we conduct experiments using two language newsgroup data sets: one written by English and the other written by Korean. Four kinds of classifiers are used in our experiments: Naive Bayes, Rocchio, k-NN, and SVM. We observe that our new method makes a significant improvement in all these classifiers and both data sets