中国科学院自动化研究所机构知识库

In  an  experimental  environment  with  limited  conditions,  it  is  always  hard to  achieve  precise  positioning  of  robotic fish. A combined indoor self-positioning method in this  paper is introduced to solve the problem. For the short-distance  range, coordinates are calculated by fusing the measured distances  and  angles. For  the  medium-distance  range,  a  clustering-grid 
supervision (CGS) algorithm is proposed and adopted to correct  the coordinates obtained by the four-point positioning method. An  ostracion-like robotic fish is used as the experimental object to  achieve centimeter-level positioning with an average positioning  error of 4.492 cm in a short-distance range and decimeter-level positioning with an error of 2.049 dm in a medium-distance range.  Compared with traditional methods, this comprehensive method  has the advantages of low cost and high accuracy.