• 대한전기학회논문지
• /
• 제41권7호
• /
• pp.809-822
• /
• 1992

A mathematical approach to solving the time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in robot joint space(JS). View-time concept is used to deal with time-varying obstacles. The view-time is the period in which a time-varying obstacles. The view-time is the period in which a time-varying obstacle is viewed and approximated by an equivalent stationary obstacle. The equivalent stationary obstacle is the volume swept by the time-varying obstacle for the view-time. The swept volume is transformed into the JS obstacle that is the set of JS robot configurations causing the collision between the robot and the swept volume. In JS, the path avoiding the JS obstacle is planned, and a trajectory satisfying the constraints on robot motion planning is planned along the path. This method is applied to the collision-free motion planning of two SCARA robots, and the simulation results are given.

• 대한전자공학회논문지
• /
• 제27권10호
• /
• pp.44-52
• /
• 1990

공간상에 움직여야할 길이 주어진 두 대의 로보트의 속도계획 문제를 두 단계의 부문제로 나누어 각각의 독립적으로 다루는 방법을 도입하여 최소시간 속도계획 방법을 제안하였다. 제안된 방법은 i) 로보트가 각자의 길을 따라 이동한 거리를 두 축으로하는 코오디네이션 공간이라는 2차원 공간을 구축하고 이공간상에서 충돌을 피할 수 있도록 코오드네이션 곡선을 선정하고, ii)선정된 곡선을 따라 최소시간을 보장하는 속도계획을 하는 두 단계의 문제중 두 번째 단계의 문제에 대해 로보트의 동력학 및 각 관절의 최대 회전속도등을 고려하여 최적해를 구하는 방법을 제안하였다. 또한 신경 최적화 회로망의 이론을 응용하여 간단한 반복 계산 알고리듬으로 최적해를 구하였다. 제안된 방법은 두 대의 SCARA형 로보트의 경로계획의 예로 시뮬레이션하여 유용성을 보였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
• /
• pp.951-957
• /
• 1988

A collision-free trajectory planning algorithm is proposed to optimally coordinate two robots working in a common 3-D workspace. Each link of the two robots is modeled as a line segment and by their motion priority, one of the two robots is chosen as the master and the other the slave. And the one-step-ahead minimum distance between the two robots is computed by moving the master to the next location on its specified trajectory. Then the nominal trajectory of the slave is modified such that the distance between the next locations of the master and the slave must be larger than a prespecified allowable minimum distance. Here the weighted sum of the trajectory error and the joint motions of the slave is minimized by using the linear programming technique under the constraints that joint angle and velocity limits are not violated. To show the validity of the proposed algorithm, a numerical example is illustrated by employing a two dof's and a three dof's planar robots.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2003년도 춘계학술대회 논문집
• /
• pp.1651-1654
• /
• 2003

The process equipment for handling high level radioactive materials, such as spent nuclear fuel, is operated within a sealed facility, called a hot cell, due to high radioactivity. Thus, this equipment should be maintained and repaired by remotely operated manipulator. In this study, to carry out the sale and effective maintenance of the process equipment installed in the hot cell by a servo type manipulator, a collision free motion planning method of the manipulator using virtual prototyping technology is suggested. To do this, the parts are modelled in 3-D graphics, assembled, and kinematics are assigned and the virtual workcell is implemented in the graphical environment which is the same as the real environment. The method proposed in this paper is to find the optimal path of the manipulator using the function of the collision detection in the graphic simulator. The proposed path planning method and this graphic simulator of manipulator can be effectively used in designing of the maintenance processes for the hot cell equipment and enhancing the reliability of the spent fuel management.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• pp.1040-1045
• /
• 1991

An approach to time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in Cartesian space and in joint space. To deal with the time-varying obstacles, view-time is introduced. A view-time is the time interval viewing the time-varying obstacles to model equivalent stationary obstacles. For the analysis of the properties of the view-time, avoidability measure is defined as a measure of easiness for a robot to avoid obstacles. Based on the properties, a motion planning strategy to avoid time-varying obstacles is derived. An application of the strategy to the collision-free motion planning of two SCARA robots and the simulation on the application are given.

• 한국정밀공학회지
• /
• 제10권2호
• /
• pp.170-177
• /
• 1993

In robotic arc welding, the roll (rotation) of the torch about its direction vector does not have any effect on the welding operation. Thus we could use this redundant degree of greedom for the motion control of the robot manipulator. This paper presents an algorithm for the pseudo- inverse kinematic motion control of the 6-axis robot, which utilizes the above mentioned redunancy. The prototype welding operation and the tool path are also graphically simulated. Since the proposed algorithm requires only the position and normal vector of the weldine as an input data, it is useful for the CAD-based off-line programming of the arc welding robot. In addition, it also has the advantages of the redundant manipulator motion control, like singularity avoidance and collision free motion planning, when compared with the other motion control method based on the direct inverse kinematics.

• Journal of Electrical Engineering and Technology
• /
• 제10권2호
• /
• pp.676-687
• /
• 2015

Path planning algorithms are used to allow mobile robots to avoid obstacles and find ways from a start point to a target point. The general path planning algorithm focused on constructing of collision free path. However, a high continuous path can make smooth and efficiently movements. To improve the continuity of the path, the searched waypoints are connected by the proposed polynomial interpolation. The existing polynomial interpolation methods connect two points. In this paper, point groups are created with three points. The point groups have each polynomial. Polynomials are made by matching the differential values and simple matrix calculation. Membership functions are used to distribute the weight of each polynomial at overlapped sections. As a result, the path has $G^2$ continuity. In addition, the proposed method can analyze path numerically to obtain curvature and heading angle. Moreover, it does not require complex calculation and databases to save the created path.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.168-173
• /
• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
• /
• 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
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• 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.