• 로봇학회논문지
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• 제2권3호
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• pp.262-269
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• 2007

Hierarchical Planning based on Abstraction of World Elements and Operators(HiPAWO) is proposed for mobile robots task planning, where abstraction of world elements is used for hierarchical planning and abstraction of operators is used for hierarchical decomposition of abstracted actions. Especially, a hierarchical domain theory based on JAH(Joint of Action Hierarchy)-graph is proposed to improve efficiency of planning, where a number of same actions are included in both adjacent hierarchical levels of domain theories to provide relationships between adjacent hierarchical levels. To show the validities of our proposed HiPAWO, experimental results are illustrated and will be compared with two other classical planning methods.

• 한국시뮬레이션학회논문지
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• 제15권2호
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• pp.1-12
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• 2006

지능형 시스템에 대한 요구가 지속적으로 증가하면서, 최근에는 인공지능과 시뮬레이션 기술을 연동하기 위한 다양한 접근이 이루어지고 있다. 본 논문의 기반이 되는 RG-DEVS는 이산 사건 시뮬레이션 모델링 방법론인 DEVS에 인공지능의 계획(planning) 기술을 반영함으로써 동적으로 시뮬레이션 모델이 정의될 수 있는 인공지능과 시뮬레이션의 연동 기술이다. 그러나, 오늘날 많은 문제 해결 시스템들에 반영되고 있는 계층성(hierarchy)이 계획에 반영되어 있지 않다. 계층성은 탐색 공간을 작게 하여 계획의 계산 비용을 줄일 수 있을 뿐 아니라, 모델링 대상 시스템의 계층적 작업 흐름을 반영하기에도 유용하다. 본 논문은 RG-DEVS에 계층적 계획 능력을 추가하여 확장한 모델링 방법론인 HRG-DEVS출 제안하고, 이를 검증하기 위하여 고전적인 계획 문제로 알려진 계층적인 블록 쌓기 문제인 ABSTRIPS에 적용하였다.

• 로봇학회논문지
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• 제16권3호
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• pp.283-290
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• 2021

We propose a task and motion planning algorithm for clearing obstacles and wiping surfaces, which is essential for surface disinfection during the pathogen disinfection process. The proposed task and motion planning algorithm determines task parameters such as grasping pose and placement location during the planning process without using pre-specified or discretized values. Furthermore, to quickly inspect many unit motions, we propose a motion feasibility prediction algorithm consisting of collision checking and an SVM model for inverse mechanics and self-collision prediction. Planning time analysis shows that the feasibility prediction algorithm can significantly increase the planning speed and success rates in situations with multiple obstacles. Finally, we implemented a hierarchical control scheme to enable wiping motion while following a planner-generated joint trajectory. We verified our planning and control framework by conducted an obstacle-clearing and surface wiping experiment in a simulated disinfection environment.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.664-668
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• 2012

Hierarchical IPP (Integrated Path Planning) combining the GPP (Global Path Planner) and the LPP (Local Path Planner) is interesting the researches who study about the mobile vehicle in recent years. However, in this study, there is the path mismatch problem caused by the difference in the map information available to both path planners. If ever a part of the path that was found by the GPP is available to mobile vehicle, the part may be unavailable when the mobile vehicle generates the local path with its built-in sensors while the vehicle moves. This paper proposed the TWR (Temporal Waypoint Reviser) to solve the path mismatch problem of the hierarchical IPP. The results of simulation provide the performance of the IPP with the TWR by comparing with other path planners.

• 한국경영과학회지
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• 제18권1호
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• pp.1-18
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• 1993

The family disaggregation model of hierarchical production planning (HPP) is the problem of (0 -1) mixed integer programming that minimizes the total sum of setup costs and inventory holding costs over the planning horizon. This problem is hard in a practical sense since optimal solution algorithms have failed to solve it within reasonable computation times. Thus effective familoy disaggregation algorithm should be developed for HPP. The family disaggregation algorithm developed in this paper consists of the first stage of finding initial solutions and the second stage of improving initial solutions. Some experimental results are given to verify the effectiveness of developed disaggregation algorithm.

• 대한전기학회논문지
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• 제39권10호
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• pp.1121-1232
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• 1990

A hierarchical neural network structure is described for robot PTP trajectory planning. In the first level, the multi-layered Perceptron neural network is used for the inverse kinematics with the back-propagation learning procedure. In the second level, a saccade generation model based joint trajectory planning model in proposed and analyzed with several features. Various simulations are performed to investigate the characteristics of the proposed neural networks.

• 한국경영과학회지
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• 제16권2호
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• pp.125-125
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• 1991

This paper presents a framework for the hierarchical PPC(Production Planning and Control) in make-to-order environment with job shop. The characteristics of the environment are described as : 1) project with non-repetitive and individual production, 2) short delivery date, 3) process layout with large scales manufacturing. 4) job shops. The PPC in a make-to-order typically are organized along hierarchical fashions. A model is proposed for the hierarchical job shop scheduling based on new concepts of production system, work and worker organization. Then, a new integrated hierarchical framework is also developed for the PPC based on concepts of the proposed job shops scheduling model. Finally, the proposed framework has been implemented in the Electric Motor Manufacturing and the results showed good performance.

• 경영과학
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• 제16권2호
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• pp.125-135
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• 1999

This paper presents a framework for the hierarchical PPC(Production Planning and Control) in make-to-order environment with job shop. The characteristics of the environment are described as : 1) project with non-repetitive and individual production, 2) short delivery date, 3) process layout with large scales manufacturing. 4) job shops. The PPC in a make-to-order typically are organized along hierarchical fashions. A model is proposed for the hierarchical job shop scheduling based on new concepts of production system, work and worker organization. Then, a new integrated hierarchical framework is also developed for the PPC based on concepts of the proposed job shops scheduling model. Finally, the proposed framework has been implemented in the Electric Motor Manufacturing and the results showed good performance.

• 대한기계학회논문집
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• 제18권8호
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• pp.2016-2025
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• 1994

A hierarchical planning strategy for dextrous manipulation of multifingered hands with soft finger contact model is proposed. Dextrous manipulation planning can be divided into a high-level stage which specifies the position/orientation trajectories of the fingertips on the object and a low-level stage which determines the contact forces and joint trajectories for the fingers. In the low-level stage, various nonlinear optimization problems are formulated according to the contact modes and integrated into a manipulation planning algorithm to find contact forces and joint velocities at each time step. Montana's contact equations are used for the high-level planning. Quasi-static simulation results are presented and illustrated by employing a three-fingered hand manipulating a sphere to demonstrate the validity of the proposed low-level planning strategy.

• 한국게임학회 논문지
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• 제8권1호
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• pp.79-90
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• 2008

본 논문에서는 동기 기반의 계층적 행동 계획 시스템을 제안한다. 가상 시뮬레이션 게임 환경에서 에이전트는 행동 계획 시스템을 통해 적합한 행동을 선택하게 된다. 행동 선택 시스템은 동기를 추출하고 목표를 선택하고 행동을 생성하고 최적화를 수행한다. 동기를 평가할 때 갑작스럽게 발생하거나 누적된 이벤트에 대해 계산한다. 동기를 선택할 때는 확률 분포를 사용하여 무작위로 선택한다. 계층적 목표 트리를 탐색한 후에 목표를 실행할 수 있다. 행동들을 비교한 후 가장 적합한 행동을 선택하게 된다. 선택을 할 때 안전도 값과 만족도 값을 비교하여 최적화된 행동을 선택한다. 본 연구에서 제안한 시스템을 식당경영 게임에 적용했다.