• The Journal of Korea Robotics Society
• /
• v.19 no.2
• /
• pp.196-202
• /
• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.10
• /
• pp.50-58
• /
• 1993

The problem of trajectory planning in two redundant robot systems is considered. The trajectory of each robot for the cooperative task is generated so that the robots assume their optimal configurations while following a given desired task. The cooperative task compatibility in and the weighted sum of manipulabilities are proposed and investigated as quality measures. The cooperative task compatibility includes the velocity and force transmission charateristics to the task requirements and so it measures the compatibilities of robot postures with respect to a given task. The weighted sum of manipuabilities of robot postures with respect to a given task. The weighted sum of manipulabilities is also considered as a quality measure since it is helpful to avoid singularities. The usefulness of the cooperative task compatibility and the weighted sum of manipulabilities are shown by computer simulation studies.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.4
• /
• pp.709-714
• /
• 2023

A flexible planning system is an important element for the robot to perform various tasks. In this paper, we introduce an automated planning system architecture that can deal with the changing environment. PDDL is used for symbolic-based task planning, and a graph database is used for real-time environment information updates for automated PDDL generation. The proposed framework was verified through scenario-based experiments.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.129-139
• /
• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.

• ETRI Journal
• /
• v.30 no.1
• /
• pp.1-12
• /
• 2008

In this paper, we propose an efficient single-resource task scheduling algorithm for the Communication, Ocean, and Meteorological Satellite. Among general satellite planning functions such as constraint check, priority check, and task scheduling, this paper focuses on the task scheduling algorithm, which resolves conflict among tasks which have an exclusion relation and the same priority. The goal of the proposed task scheduling algorithm is to maximize the number of tasks that can be scheduled. The rationale of the algorithm is that a discarded task can be scheduled instead of a previously selected one depending on the expected benefit acquired by doing so. The evaluation results show that the proposed algorithm enhances the number of tasks that can be scheduled considerably.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.9 no.3
• /
• pp.206-212
• /
• 2009

This paper presents an optimized integrated task planning and control approach for manipulating a nonholonomic robot by mobile manipulators. Then, we derive a kinematics model and a mobility of the mobile manipulator(M2) platform considering it as the combined system of the manipulator and the mobile robot. to improve task execution efficiency utilizing the redundancy, optimal trajectory of the mobile manipulator(M2) platform are maintained while it is moving to a new task point. A cost function for optimality can be defined as a combination of the square errors of the desired and actual configurations of the mobile robot and of the task robot. In the combination of the two square errors, a newly defined mobility of a mobile robot is utilized as a weighting index. With the aid of the gradient method, the cost function is minimized, so the path trajectory that the M2 platform generates is optimized. The simulation results of the 2 ink planar nonholonomic M2 platform are given to show the effectiveness of the proposed algorithm.

• Journal of Institute of Convergence Technology
• /
• v.6 no.2
• /
• pp.9-13
• /
• 2016

Robot usually requires spline motion to move through multiple knots. In this paper, catmull-rom spline method is applied to the trajectory planning of industrial robot in task space. Centripetal catmull-rom is selected to avoid self-intersection and slow motion which can be occurred in uniform and chordal spline. The method to set two control points are proposed to satisfy velocity conditions of initial and final knots. To optimize robot motion, time scaling method is presented to minimize margin between real robot value and maximum value in velocity and acceleration. The simulation results show that the proposed methods are applied to trajectory planning and robot can follow the planned trajectory while robot motion does not exceed maximum value of velocity and acceleration.

• Asia pacific journal of information systems
• /
• v.3 no.2
• /
• pp.117-144
• /
• 1993

MIS researches involve, in particular, the problems of developing appropriate IS for given MIS environments and lay emphasis on identifying prominant IS characteristics pertaining to the system in issue. This study deals with the IS characteristics for the management task of "planning". It investigates empirically the impacts of IS characteristics, under a set of proposed hypotheses, with particular respect to users' information satisfaction and performance in carrying out the task of planning. Futhermore, it examines whether the IS characteristics have different effects depending on the planning modes on the part of IS users. Based on a group of hypotheses accepted, the IS characteristics for planning decision making are not only proposed according to planning modes: preactive, reactive and proactive, but also classified into six subsystem categories: input, process, ouput, storage, interface and communication. Finally, the implications of the findings are discussed.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.3
• /
• pp.401-412
• /
• 2008

This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2846-2848
• /
• 2000

In this paper we propose a path planning method for an autonomous mobile robot based on genetic algorithms(GAs). There have been a number of methods proposed for the path planning of a mobile robot. However, few algorithms have been developed for an on-line path planning of a mobile robot with the uncertain information of a task environment. Therefore, we propose a path planning algorithms based on GAs that has ability of creating path planning without the perfect information of a task environment and an ability of planning the efficient path by on-line process. Then we show a possibility of the practical use with the results of simulations and experiments.