본 연구는 기존 노인용 기능성 게임이 갖는 장점과 한계점을 분석하고 체감형 게임이 갖는 매체적 가능성을 접목하여 노인용 체감형 기능성 게임의 스토리텔링 전략을 탐색하는 것을 목적으로 한다. 따라서 본 연구는 노인용 기능성 게임에 대한 이론적 탐색과 경험적인 접근을 바탕으로, 노인이라는 대상의 특수성과 체감 인터페이스라는 기술적 속성, 그리고 재미와 기능이라는 이질적인 두 속성의 결합이 만들어내는 혼재성을, 게임의 형식으로 구조화하기 위해 스토리텔링 전략을 수립하고 게임을 기획하였다. <The four seasons>는 동작인식센서 키넥트를 활용한 재활치료용 체감형 기능성 게임이다. 지루하고 힘든 재활치료를 재미있게 훈련할 수 있는 체감형 기능성 게임으로 편마비 재활 치료를 위한 동작을 반복할수록 스크린 너머 가상세계가 풍요로워진다. 게임 플레이 과정은 뇌졸중으로 인해 편마비가 있는 중, 장년층이나 신체의 움직임이 원활하지 못한 노인들에게 정신적 위안과 신체적 건강을 얻게 한다. <The four seasons>게임은 감정 유희와 동작 유희가 인과적으로 연결 된 게임으로 동기부여, 동작반복, 피드백의 순환이 게임 내적 매커니즘을 통해 흥미롭게 전개되도록 하기 위해 특정 감정을 의도적으로 이끌어내고 그에 따른 결과로 행동을 유도한다. 본 연구 에서는 <The Four Seasons>의 스토리텔링 기획 과정을 체계적으로 기술함으로써 노인용 체감형 기능성 게임의 실제적 개선을 위한 스토리텔링의 구체적 방법론과 새로운 방향성을 모색하고자 하였다.

Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

In general, the attitude of a high-speed planning boat changes following a speed change. Since the hydrodynamic forces acting on a ship differ according to the change of its underwater shape, it is difficult to estimate its hydrodynamic force compared to that of a large commercial ship. In this paper, 6 Degrees Of Freedom (DOF) equations of motion that express the maneuvering motion of a planning boat are modeled by analyzing its motion characteristics based on various sea trial tests. Finally, a maneuvering simulation is carried out and a validation of the equations of motion is confirmed with the results of sea trial tests.

This paper presents a method to optimize motion planning for industrial manipulators with redundancy. For optimal motion planning, first of all, particular inverse kinematic solution is needed to improve efficiency for manipulators with redundancy working in various environments. In this paper, we propose three kinds of methods for solving inverse kinematics problems; numerical and combined approach. Also, we introduce methods for optimal motion planning using potential function considering the order of priority. For efficient movement in industrial settings, this paper presents methods to plan motions by considering colliding obstacles, joint limits, and interference between whole arms. To confirm improved performance of robot applying the proposed algorithms, we use two kinds of robots with redundancy. One is a single arm robot with 7DOF and another is a dual arm robot with 15DOF which consists of left arm, right arm with each 7DOF, and a torso part with 1DOF. The proposed algorithms are verified through several numerical examples as well as by real implementation in robot controllers.

This work deals with development of effective redundancy resolution algorithms for the motion control of manipulator. Differently from the typical kinematically redundant robots that are attached to the fixed ground, the ZMP condition should be taken into account in the manipulator motion in order to guarantee the system stability. In this paper, a new motion planning algorithm for redundant manipulator not fixed to the ground is introduced. A sequential redundancy resolution algorithm is proposed, which ensures the ZMP (Zero Moment Point) stability, the planned operational motion, and additional sub‐criteria such as joint limit index. A geometric constraint equation derived by reshaping the existing ZMP equation enables one to employ the sequential redundancy algorithm. The feasibility of the proposed algorithm is verified by simulating a redundant manipulator model.

Automatic parking assist system is one of the key technologies of the future automobiles. Control problem of a car-like vehicle is not easy due to the nonholonomic constraints. In this paper, a practical solution for planning a car-parking path is proposed according to the proposed motion space (M-space) approach. The M-space is the extension of the conventional configuration space(C-space). A collision-free, nonholonomic feasible path can be directly computed by the M-space conversion and a back-propagation of reachable regions from the goal. the proposed planning scheme provide not a single solution, but also a candidate solution set, therefore, optimization of the parking path can beeasily carried out with respect to performance criteria such as safety, maneuvering, and so on. Presented simulation results clearly show that the proposed scheme provides various practical solutions.

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

Effective tools which can alleviate the complexity and computational load problem in collision-free motion planning for multi-agent system have steadily been demanded in robotics field. To reduce the complexity, the extended collision map (ECM) which adopts decoupled approach and prioritization is already proposed. In ECM, the collision regions which represent the potential collision of robots are calculated using the computational power; the complexity problem is not resolved completely. In this paper, we propose a mathematical analysis of the extended collision map; as a result, we formulate the collision region as an equation with 5–8 variables. For mathematical analysis, we introduce realistic assumptions as follows; the paths of robots can be approximated to a straight line or an arc and the robots move with uniform velocity or constant acceleration near the intersection between paths. Our result reduces the computational complexity in comparison with the previous result without losing optimality, because we use simple but exact equations of the collision regions. This result can be widely applicable to coordinated multi-agent motion planning.

During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate humanlike arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.

It is well known that mathematical solutions for multi-agent planning problems are very difficult to obtain due to the complexity of mutual interactions among multi-agent. Most of the past research results thus are based on the probabilistic completeness. However, the practicality and effectiveness of the solution from the probabilistic completeness is significantly reduced by heavy computational burden. In this paper, we propose a practically applicable solution technique for multi-agent planning problems, which assures a reasonable computation time and a real world application for more than 3 multi-agents for the case of general shaped paths in agent movement. First, to reduce the computation time, a collision map is utilized for detecting potential collisions and obtaining collision-free solutions for multi-agents. Second, to minimize the maximum of multi-agent task execution time, a method is developed for selecting an optimal priority order. Simulations are finally provided for more than 20 agents to emphasize the effectiveness of the proposed interactive approach to multi-agent planning problems.