Collision-avoidance Control Based on Gaussian Distribution and Superquadric Modeling

• Main Authors: Tsai, Ming-Dar, 蔡明達
• Other Authors: Kao-Shing Hwang
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/79377507116657978687

碩士 === 國立中正大學 === 電機工程學系 === 84 === In this thesis, a method based on the combination of Gaussian distribution and superquadric modeling for collision-avoidance control is proposed. In order to avoid collisions among obstacles in path planning of a mobile robot, the defined collisionprobability by Gaussian distribution and the searching algorithm improved by the defined objective function have extended the applications from 2-D to 3-D working space progressively. To avoid collision between two general robot manipulators, links of the robots are modeled with simple superquadric ellipse in 2-D and ellipsoid in 3-D for simple mathematical representation and geometric approximation. From the simple modeling algorithm and the application of coordinate transformation, a fast collision-detection algorithm is introduced. Based on the algorithm, a method of controlling the speed of one robot to avoid collision with the other one, which is assumed to move at constant speed, has been applied gradually from two-joint robots in 2-D to Motoman robots with 5 DOF in 3-D. In the process of searching the optimal resolution, the collision probability defined by the combination of Gaussian distribution and superquadric modeling plays a very significant role.