• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.504-510
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• 2016

Robots are widely utilized in many fields, and various demands need customized robots. This study proposes an optimal design method based on swarm intelligence for selecting the kinematic parameter of a manipulator according to the task space trajectory desired by the user. The optimal design method is dealt with herein as an optimization problem. This study is based on swarm intelligence-based optimization algorithms (i.e., ant colony optimization (ACO) and particle swarm optimization algorithms) to determine the optimal kinematic parameters of the manipulator. The former is used to select the optimal kinematic parameter values, whereas the latter is utilized to solve the inverse kinematic problem when the ACO determines the parameter values. This study solves a design problem with the PUMA 560 when the desired task space trajectory is given and discusses its results in the simulation part to verify the performance of the proposed design.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.297-303
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• 2007

In this paper, we discuss a service to give alarm in the case of emergency for the old and the weak by human behavior recognition in Intelligent Space. Our Intelligent Space consists of mobile robots, sensors and agents. And these components are connected to network framework. Agent analyzes data acquired from networked sensors and determines task of robots and a space to provide a service for humans. In our emergency alarm service, human behavior recognition service module analyzes accelerometer data obtained from body-attached human behavior sensing platform, and classifies into four basic human behavior such as walking, running, sitting and falling-down. For the old and the weak, falling-down behavior may bring about dangerous situations. On such an occasion, agent executes emergency alarm service immediately. And then a selected mobile robot approaches fallen person and sends images of the person to guardians. In this paper, we set up a scenario to verify the emergency alarm service in Intelligent Space, and show feasibility of the service from our simulation experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3423-3438
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• 2014

In recent years, wearable sensor devices are reshaping the way people live, work, and play. A wearable sensor device is a computer that is subsumed into the personal space of the user, and is always on, and always accessible. Therefore, among the most salient aspects of a wearable sensor device should be a small form factor, long battery lifetime, and real-time characteristics. Thereby, sophisticated applications of a wearable sensor device use real-time operating systems to guarantee real-time deadlines. The deterministic multi-dimensional task scheduling algorithms are implemented on ARC (Actual Remote Control) with relatively limited hardware resources. ARC is a wearable wristwatch-type remote controller; it can also serve as a universal remote control, for various wearable sensor devices. In the proposed algorithms, there is no limit on the maximum number of task priorities, and the memory requirement can be dramatically reduced. Furthermore, regardless of the number of tasks, the complexity of the time and space of the proposed algorithms is O(1). A valuable contribution of this work is to guarantee real-time deadlines for wearable sensor devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.31-48
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• 2023

The popularization of smart devices and subsequent optimization of their sensing capacity has resulted in a novel mobile crowdsensing (MCS) pattern, which employs smart devices as sensing nodes by recruiting users to develop a sensing network for multiple-task performance. This technique has garnered much scholarly interest in terms of sensing range, cost, and integration. The MCS is prevalent in various fields, including environmental monitoring, noise monitoring, and road monitoring. A complete MCS life cycle entails task allocation, data collection, and data aggregation. Regardless, specific drawbacks remain unresolved in this study despite extensive research on this life cycle. This article mainly summarizes single-task, multi-task allocation, and space-time multi-task allocation at the task allocation stage. Meanwhile, the quality, safety, and efficiency of data collection are discussed at the data collection stage. Edge computing, which provides a novel development idea to derive data from the MCS system, is also highlighted. Furthermore, data aggregation security and quality are summarized at the data aggregation stage. The novel development of multi-modal data aggregation is also outlined following the diversity of data obtained from MCS. Overall, this article summarizes the three aspects of the MCS life cycle, analyzes the issues underlying this study, and offers developmental directions for future scholars' reference.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.739-742
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• 1996

Several figures representing velocity transmission from joint space to task space are analyzed and compared with each other. The figures include velocity ellipsoid derived from Jacobian matrix, scaled velocity ellipsoid derived from normalized joint velocities, polytope derived by numerical scaling, and polytopes derived by linear combinations of Jacobian column vectors. The results show that the optimal directions given by the measures are not the same and the conventional velocity ellipsoid is not good choice as optimization measure as far as the moving direction is concerned. Simulation examples for 3 d.o.f. redundant robot manipulators in 2-dimensional task space are given for comparison study.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.37-45
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• 1992

For a precise manipulator control in the presence of environmental uncertainties, it has long been recognized that the robot should be controlled in a task-referenced space. In this respect, an effective visual servo control system for robot manipulators based on neural networks is proposed. In the proposed control system, a Backpropagation neural network is used first to learn the mapping relationship between the robot's joint space and the video image space. However, in the real control loop, this network is not used in itself, but its first and second derivatives are used to generate servo commands for the robot. Second, and Adaline neural network is used to identify the approximately linear dynamics of the robot and also to generate the proper joint torque commands. Computer simulation has been performed demonstrating the proposed method's superior performance. Futrhermore, the proposed scheme can be effectively utilized in a robot skill acquisition system where the robot can be taught by watching a human behavioral task.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.333-338
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• 2009

This paper presents a task-based analysis on the number of independent robotic fingers required for compliant manipulations. Based on the stiffness relation between operational space and fingertip space of a multi-fingered object manipulating system, we describe a technique for modulation of the fingertip stiffness without inter-finger coupling so as to achieve the desired stiffness specified in the operational space. Thus, we provides a guide line how many fingers are basically required for successful multi-fingered compliant tasks. Consequently, this paper enables us to assign effectively the number of fingers for various compliant manipulations by robot hands.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.64-71
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• 2004

A daily report is one of the critical documents in construction projects, since it helps them keep track of various as-built information. Despite the important role in progress management, the daily reporting process is time-consuming, and the representation of task information on daily reports are not effective enough to accumulate daily as-built information for further use in project management. Task information is composed of a specific work type and a location where the task is performed, which means that the same type of work is repeated over the locations. However, in many cases the task locations are described differently depending on a reporter's preference or experience. Without representing task location information effectively, it is difficult to accumulate and to reuse as-built information. The objective of this research is to build a framework for generating task information which can be efficiently accumulated and reused for progress management. To do so, this research built a task information model with focusing on the representation of task location associated with a work type, and developed an information system that supports automated and interactive generation of task information.

• Journal of the Korean earth science society
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• v.30 no.1
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• pp.141-151
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• 2009

Inquiry has been emphasized in science classrooms, but the problems shown in the inquiry are somewhat different with ones that students usually meet and experience in everyday life. The purpose of this study is to investigate how attitudes toward the task and thinking skills affect students' problem solving process, especially, the way of creating a problem space and elaborating problem solving strategies when they have little schema. The difference in students' problem solving strategies of Lego Robotics class, one of the summer programs for $4^{th}-6^{th}$ grade gifted students, which is new to them, was investigated. The results are as follows: (1) The difference in attitudes toward the task, or selection and identification of the missions, and the perception of operators, affected creating a different problem space. (2) Different level of thinking skills, or analytical and flexible thinking, efficient elaborative skill, and application of schema affected a different level of elaboration of the problem space and resulted in asuccess rate of problem solving. (3) Different initial problem space resulted in different problem solving strategies. But without thinking skills, students could not elaborate problem solving strategies efficiently. Several instructional recommendations to promote scientific inquiry were suggested based on the results.