• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
• /
• pp.392-395
• /
• 1995

This paper presents a time efficient method for determining a sequence of locations of a mobile manipulator that facilitates tracking of continuous path in cluttered environment. Given the task trajectory in the form of octree data structure, the algorithm performs characterization of task space and subsequent multistage optimization process to determine task feasible locations of the robot. Firstly, the collision free portion of the trajectory is determined and classified according to uniqueness domains of the inverse kinematics solutions. Then by implementing the extent of task feasible subspace into an optimization criteria, a multistage optimization problem is formulated to determines the task feasible locations of the mobile manipulator. The effectiveness of the proposed method is shown through a simulation study performed for a 3-d.o.f. manipulator with generic kinematic structure.

• 한국공작기계학회논문집
• /
• 제17권3호
• /
• pp.1-7
• /
• 2008

This paper describes the kinematics which is a new type of parallel manipulator, and the neural network is applied to solving the forward kinematics problem. The parallel manipulator called it as a Stewart platform has an easy and unique solution about the inverse kinematics. However, the forward kinematics is difficult to get a solution because of the lack of an efficient algorithm caused by its highly nonlinearity. This paper proposes the neural network scheme of an Newton-Raphson method alternatively. It is found that the neural network can be improved its accuracy by adjusting the offset of the obtained result.

• 전자공학회논문지B
• /
• 제28B권9호
• /
• pp.739-746
• /
• 1991

This paper develops a modified multilayer perceptron architecture which speeds up learning as well as the net's mapping accuracy. In Phase I, a cluster partitioning algorithm like the Kohonen's self-organizing feature map or the leader clustering algorithm is used as the front end that determines the cluster to which the input data belongs. In Phase II, this cluster selects a subset of the hidden layer nodes that combines the input and outputs nodes into a subnet of the full scale backpropagation network. The proposed net has been applied to two mapping problems, one rather smooth and the other highly nonlinear. Namely, the inverse kinematic problem for a 3-link robot manipulator and the 5-bit parity mapping have been chosen as examples. The results demonstrate the proposed net's superior accuracy and convergence properties over the original backpropagation network or its existing improvement techniques.

• 한국자동차공학회논문집
• /
• 제2권6호
• /
• pp.57-65
• /
• 1994

A collision-free path planning algorithm between an articulated robot and polyhedral obstacles using configuration space is presented. In configuration space, a robot is treated as a point and obstacles are treated as grown forbidden regions. Hence path planning problem is transformed into moving a point from start position to goal position without entering forbidden regions. For mapping to 3D joint space, slice projection method is used for first revolute joint and inverse kinematics is used for second and third revolute joint considering kinematic characteristics of industrial robot. Also, three projected 2D joint spaces are used in search of collision-free path. A proper example is provided to illustrate the proposed algorithm.