Network Robot System Research Articles

Effect analysis of neural network robot system in music relaxation training to alleviate adverse reactions of chemotherapy in patients with breast cancer.

Music therapy is a common method to relieve anxiety and pain in cancer patients after surgery in recent years, but due to the lack of technical and algorithmic support, this therapy is not particularly stable and the therapeutic effect is not good. In this study, a neural network robotic system based on breast cancer patients was designed to analyze the effect of music relaxation training on alleviating adverse reactions after chemotherapy in breast cancer patients. Firstly, this paper introduces the necessity of neural network robot system research under the background of music therapy, and then summarizes the positive effect of music relaxation therapy on alleviating adverse reactions after chemotherapy in breast cancer patients, finally, uses neural network robot system to construct music therapy system. The experimental results show that the new music therapy proposed in this study has a good effect in alleviating the adverse reactions of breast cancer patients after chemotherapy, and the cure rate is increased by 7.84%. The research results of this paper provide reference for the next development of neural network robot system in the medical field.

An Overview of Network Robot System and Its Applications

A robot capable of performing multiple tasks is a multi-purpose device with one or more arms and joints. Robots are similar to humans, but industrial robots do not resemble humans. Any machine that operates automatically that modifies human effort is a robot that does not look or resemble humans in appearance or perform human-like functions. In a nutshell, The full layout of ROBOT consists of a movable body system, a motor, which controls all of these organs is the "brain". Basically, the engineering department handles construction and operation. Reflect the behavior of humans and animals. Robotics, layout, production and use of machines (robots) to perform responsibilities traditionally carried out by humans. Robots are extensively used in industries which include automotive manufacturing, and in industries that require them to perform easy obligations and work in hazardous environments. The six most common kinds of robots are self sustaining cellular robots (AMRs), automatic guided motors (AGVs), exposed robots, human figures, robots and hybrids. Are robots used to power performance, speed up procedures, enhance safety, and enhance experience in more than one industry. One of the key factors controlling how an industrial robot moves and its workplace is its robot structure. There are six main types of robot structures: Cartesian, cylindrical, spherical, and selectively compatible articulated robotic arm (SCARA). Articulate, and the delta (parallel) is a human-like machine and the machine performs routine tasks according to command. A person who acts mechanically, routinely and responsibly, usually subject to the will of another; Automatic. Robots are often controlled wirelessly or autonomously using tether (wire). The easiest way to control a robot is to use a hand-held controller that is physically attached to the robot using wires or cable. What are robotics and robotics? A robot is Any device that transforms human effort, although it no longer appears like someone in look or perform the same capabilities as someone. As a discipline, Robotics offers the layout, construction and operation of robots.

Sales Support by Using A Network Robot System and A Character Contents

Sales Support by Using A Network Robot System and A Character Contents

Research on Simultaneous Localization, Calibration and Mapping of Network Robot System

In a network robot system, a robot and a sensor network are integrated smoothly to develop their advantages and benefit from each other. Robot localization, sensor network calibration and environment mapping are three coupled issues to be solved once network robot system is introduced into a service environment. In this article, the problem of simultaneous localization, calibration and mapping is raised in order to improve their precision. The coupled relations among localization, calibration and mapping are denoted as a joint conditional distribution and then decomposed into three separate analytic terms according to Bayesian and Markov properties. The framework of Rao-Blackwellized particle filtering is used to solve the three analytic terms, in which extended particle filter is used for localization and unscented Kalman filter is used for both calibration and mapping. Simulations have been performed to demonstrate the validity and efficiency of the proposed solutions.

The Network Robot System: Enabling Social Human-Robot Interaction in Public Spaces

What kind of framework is needed to realize social robot applications in real public environments? Based on several years of experience in conducting field studies with social robots in public spaces, we identify key considerations that we have found to be indispensable in the development of robot services. We present a "network robot system" framework, which supports social robot services in five ways: observation of human behavior using environmental sensor networks, structured knowledge sharing, centralized resource and service allocation, global path planning for coordination between robots, and support for selected recognition and decision tasks by a human operator. We describe our network robot system implementation and present a demonstration in a shopping mall, illustrating how such a network robot system framework can be used to support heterogeneous teams of robots providing services in a real public environment.

Cooperative customer navigation between robots outside and inside a retail shop—an implementation on the ubiquitous market platform

Applying the technologies of a network robot system, recommendation methods used in e-commerce are incorporated in a retail shop in the real world. We constructed a platform for ubiquitous networked robots that focuses on a shop environment where communication robots perform customer navigation. The platform observes customers’ purchasing behavior by networked sensors, including a laser range finder-based human position tracking system, and then controls visible-type communication robots in the environment to perform customer navigation. Two types of navigation scenarios are implemented and investigated in experiments using 80 participants. The results indicate that the participants in the cooperative navigation scenario, who interacted with communication robots located both outside and inside the shop, felt friendliness toward the robots and found it easy to understand what the robots said.

UBIQUITOUS AND COOPERATIVE NETWORK ROBOT SYSTEM WITHIN A SERVICE FRAMEWORK

Network robot system (NRS) is a new concept that integrates physical autonomous robots, environmental sensors, and human–robot interactions through network-based cooperation. The aim of this paper is to provide a ubiquitous and cooperative service framework for NRS. We first present foundational concepts of semantic map and service definition for the framework. Then, in order to generate feasible service configurations to fulfill tasks, we propose service configuration and reconfiguration algorithms, which dynamically search the appropriate service configurations for different tasks. Additionally, we put forward a service reasoning and enabling process to tackle the service unavailable problems. A cost evaluation function for service configuration is also proposed to facilitate the selection of suitable configurations. We tested and evaluated the framework in both simulation system and physical environment. Specifically, by separately varying the parameter settings, system performance was measured in three aspects: the success rate of tasks, the average waiting time per task, and the average cost per task. The experiment results indicate that the versatile service framework provides self-adaptive capability and utilizes available resources efficiently under a range of different scenarios.

複数の案内ロボットが連携してサービス提供するネットワークロボットシステムの実現

In this paper, we report a field trial with a network robot system in a shopping mall. Our network robot system consists of three components: environmental sensors, network robot platform and social robots. Multiple laser range finders are used as the environmental sensors to estimate people's positions. Position data is used to estimate such human walking behaviors as “stopping” or “idle walking,” to direct robots to provide appropriate tasks to appropriate people. By using this information, the network robot platform coordinates multiple social robots to provide efficient service to customers. It coordinates the tasks of robots based on their positions and people's walking behavior, the paths of robots, and the conversation-performance between two robots. Each social robot interacts with people to provide recommendation information about shops and route information of the mall. The system sometimes simultaneously uses two robots to lead people from one place to the specific shop. We conducted a field trial in a shopping mall, in which four robots interacted with 414 people. It demonstrated the effectiveness of the network robot system for guiding people around a shopping mall as well as increasing their interest.

A Communication Robot in a Shopping Mall

This paper reports our development of a communication robot for use in a shopping mall to provide shopping information, offer route guidance, and build rapport. In the development, the major difficulties included sensing human behaviors, conversation in a noisy daily environment, and the needs of unexpected miscellaneous knowledge in the conversation. We chose a network-robot system approach, where a single robot's poor sensing capability and knowledge are supplemented by ubiquitous sensors and a human operator. The developed robot system detects a person with floor sensors to initiate interaction, identifies individuals with radio-frequency identification (RFID) tags, gives shopping information while chatting, and provides route guidance with deictic gestures. The robot was partially teleoperated to avoid the difficulty of speech recognition as well as to furnish a new kind of knowledge that only humans can flexibly provide. The information supplied by a human operator was later used to increase the robot's autonomy. For 25 days in a shopping mall, we conducted a field trial and gathered 2642 interactions. A total of 235 participants signed up to use RFID tags and, later, provided questionnaire responses. The questionnaire results are promising in terms of the visitors' perceived acceptability as well as the encouragement of their shopping activities. The results of the teleoperation analysis revealed that the amount of teleoperation gradually decreased, which is also promising.

Autonomous functional configuration of a network robot system

We consider distributed systems of networked robots in which: (1) each robot includes sensing, acting and/or processing modular functionalities; and (2) robots can help each other by offering those functionalities. A functional configuration is any way to allocate and connect functionalities among the robots. An interesting feature of a system of this type is the possibility to use different functional configurations to make the same set of robots perform different tasks, or to perform the same task under different conditions. In this paper, we propose an approach to automatically generate at run time a functional configuration of a network robot system to perform a given task in a given environment, and to dynamically change this configuration in response to failures. Our approach is based on artificial intelligence planning techniques, and it is provably sound, complete and optimal. Moreover, our configuration planner can be combined with an action planner to deal with tasks that require sequences of configurations. We illustrate our approach on a specific type of network robot system, called Peis-Ecology, and show experiments in which a sequence of configurations is automatically generated and executed on real robots. These experiments demonstrate that our self-configuration approach can help the system to achieve greater autonomy, flexibility and robustness.

Human behavior recognition using unconscious cameras and a visible robot in a network robot system

We developed a network robot system integrating various types of robots via ubiquitous networks that introduce an interactive robot into areas in which people are located. In this paper, we present a human behavior recognition method necessary for providing guidance in a public space, which uses a tangible network robot system composed of a mobile robot and vision sensors embedded in an environment. We define some basic features that a person typically exhibits when in need of guidance. Various human behaviors were successfully interpreted by first recognizing the basic features and then forming their different combinations.

A probabilistic framework for entire WSN localization using a mobile robot

This paper presents a new method for the localization of a Wireless Sensor Network (WSN) by means of collaboration with a robot within a Network Robot System (NRS). The method employs the signal strength as input, and has two steps: an initial estimation of the position of the nodes is obtained centrally by one robot and is based on particle filtering. It does not require any prior information about the position of the nodes. In the second stage, the nodes refine their position estimates employing a decentralized information filter. The paper shows how the method is able to recover the 3D position of the nodes, and is very suitable for WSN outdoor applications. The paper includes several implementation aspects and experimental results.

1A1-F09 ネットワークロボットを利用した体操補助システム(ネットワークロボティクス)

A network robot system integrating various types of robots via ubiquitous networks is a new concept which introduces an interactive robot living together with people, and will provide desired services at the appropriate time. In this paper, we present a gymnastics system using network robots and show experimental results. The system recognizes the motion of a person in cooperation with a network robot platform and two visible robots encourage the person to exercise effectively according to recognized human motion activity.

Humatronics Step1- 見まね学習による感性表現の獲得と人間支援ネットワークロボットシステムへの応用

Humatronics Step1- 見まね学習による感性表現の獲得と人間支援ネットワークロボットシステムへの応用

1P1-C01 ネットワークロボットシステムにおけるFDMLデータ作成コンポーネントの開発(RTミドルウェアとオープンシステム)

1P1-C01 ネットワークロボットシステムにおけるFDMLデータ作成コンポーネントの開発(RTミドルウェアとオープンシステム)