Mathematical-based Benchmarking and Performance Improvement for ANT Exploration Algorithm

摘要：

Exploration robots are sent inside collapsed building in search of trapped victims. Once inside, they have to explore the entire maze of obstacles and debris as quickly as possible without missing any accessible area by means of the search algorithm. Comparing the performances of emerging search algorithms against known benchmarks, inside realistic simulated fields are crucial for fast victim localisation. In this paper we apply the ridge regression to compute the coefficient of relationship between the “ANT victim discovery time step and the “search field complexity. The estimated coefficients allow us to predict the victim discovery time step of ANT exploration algorithm inside various generated search fields. By means of our coefficients we improve the ANT performances by introducing the Extended ANT exploration (EANT). We also evaluate EANT performances by comparing them with the performances of other existing algorithms.

关键词： exploration agent benchmark prediction weight

作者: Panteha Saeedi Soren Aksel Sorensen

作者单位: Computer Science Department University College London London,UK

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 859-864

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）