• The Journal of Korean Institute for Practical Engineering Education
• /
• v.1 no.1
• /
• pp.91-98
• /
• 2009

In approach of human-robot interaction, it is importance task in future robot industry to make to robot recognize, express, coping the emotions. The purpose of this study was to examination the effects unconscious positive and negative emotion of information processing of motor program. 13 participants(male=11, female=2) viewed smile-face picture and angry-face picture priming at 10ms level, and then performanced button press, button press and one tennis ball hitting, and button press and two tennis ball hitting task. The results appeared that positive emotion triggered more fast RT than negative emotion in planning complex motor program. Possible explanations for the performance differences depended on emotion are discussed and future research directions were provided.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.555-561
• /
• 2008

This Paper introduces new approach to develop fast and reliable gaits for quadruped robot using GA(genetic algorithm). Planning gaits for legged robots is a challenging task that requires optimizing parameters in a highly irregular and multidimensional space. Recent approaches have problems to select proper parameters which are not known in advance and optimize more than ten to twenty parameters simultaneously. In our approach, the effects of major gait parameters are analysed and used to guide the search more efficiently. The experiments of Sony AIBO ERS-7 in Webots environment indicate that our approach is able to produce much improved results in fast velocity and reliability.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1483-1490
• /
• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1939-1943
• /
• 1991

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.79-84
• /
• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.6
• /
• pp.2760-2769
• /
• 2011

An intelligent autonomous robot generates a plan to achieve a goal. A plan is a sequence of robot actions that accomplish a given mission by being successfully executed. However, in the complex and dynamic real world, a robot may encounter unexpected situations and may not execute its planned actions any more. Therefore, an intelligent autonomous robot must prepare an efficient handling process to cope with these situations to successfully complete a given mission. Plan repair with milestone states is an efficient method to cope with the situation. It retains the advantages of other plan repair procedures. This paper proposes a regressive method of formulating milestone states and a method of assigning weighting values on conditions that compose a milestone state. The task to repair a plan may employ the weighting values as its job priority. The regressive method formulates less complex milestone states and leads to the conditions of a milestone state to take pertinent weighting values for an efficient handling procedure to repair a plan with milestone states.

• The KIPS Transactions:PartB
• /
• v.15B no.2
• /
• pp.159-170
• /
• 2008

Nowadays, one of the important functionalities required from robot task planners is to generate plans to compose existing component services into a new service. In this paper, we introduce the design and implementation of a heuristic search planner, JPLAN, as a kernel module for component service composition. JPLAN uses a local search algorithm and planning graph heuristics. The local search algorithm, EHC+, is an extended version of the Enforced Hill-Climbing(EHC) which have shown high efficiency applied in state-space planners including FF. It requires some amount of additional local search, but it is expected to reduce overall amount of search to arrive at a goal state and get shorter plans. We also present some effective heuristic extraction methods which are necessarily needed for search on a large state-space. The heuristic extraction methods utilize planning graphs that have been first used for plan generation in Graphplan. We introduce some planning graph heuristics and then analyze their effects on plan generation through experiments.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2148-2153
• /
• 2005

For a legged robot such as a humanoid, balancing its body during a given motion is natural but the most important problem. Recently, a motion given to a humanoid is more and more complicated, and thus the balancing problem becomes much more critical. This paper suggests a real-time motion generation algorithm that guarantees a humanoid to be balanced during the motion. A desired motion of each arm and/or leg is planned by the conventional motion planning method without considering the balancing problem. In order to balance a humanoid, all the given motions are embedded into the COG Jacobian. The COG Jacobian is modified to include the desired motions and, in consequence, dimension of the COG Jacobian is drastically reduced. With the motion-embedded COG Jacobian, balancing and performing a task is completed simultaneously, without changing any other parameters related to the control or planning. Validity and efficiency of the proposed motion-embedded COG Jacobian is simulated in the paper.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.295-298
• /
• 2010

Linear Temporal Logic synthesis 는 LTL formula 로 표현된 요구 사항으로부터 그것을 만족하는 시스템을 만들어낸다. 이러한 synthesis 과정은 2EXPTIME-complete 이 요구 되지만 GR formula 라는 특수한 형태를 사용함으로써 복잡도를 Polynomial 시간으로 줄일 수 있다. LTL synthesis 는 작업 공간, 로봇이 취하는 센서 정보와 액션의 종류, 상위 수준의 작업 명세를 입력으로 받아 GR formula 형태로 변환하고, 기대되는 작업이 실현 가능하다면 그것을 성취할 수 있는 오토마타를 생성해낸다. Synthesis 알고리즘을 구현한 LTLMoP 라는 도구를 이용하여 LTL synthesis 과정을 보이고 화성 행궁의 미아 찾기 로봇 작업 계획을 구현한다. 마지막으로 시뮬레이션 과정을 통해 기대하는 작업을 성공적으로 성취할 수 있음을 보인다.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.1
• /
• pp.363-375
• /
• 2013

Today, a shortage of the skilled operator has been intensified gradually and the necessity of an earthwork in extreme environment operators are difficult to access is increasing for the purpose of resource development and new living space creation. For this reason, an effort to develop an unmanned excavation robot for fully automated earthwork system is continuing globally. In Korea, a research consortium called 'Intelligent Excavation System' has been formed since 2006 as a part of Construction Technology Innovation Program of Ministry of Land, Transport and Maritime Affairs of Korea. Among detailed technologies of the Task Planning System is one of the core technologies of IES, this paper explains research and development process of the Local Area Design Module, which provides informatization unit to create automated excavators' work command information at operation level such as location, range, target, and sequence for excavation work. Designing of Local Area should be considered various influential factors such as excavator's specification, working mechanism, heuristics, and structural stability to create work plan guaranteed safety and effectiveness. For this research, conceptual and detail design of the Local Area is performed for analyzing design element and variable, and quantization method of design specification corresponding with heuristics and structural safety is generated. Finally, module is developed through constructed algorithm and developed module is verified.