摘要
采用进化算法和基于自主视觉的适应度评估方法,实现了四腿机器人在RoboCup机器人足球比赛现场的行走步态在线自动进化.我们引入内推法作为交叉方法,利用PC基站进行进化算法计算和流程主控,并采用了一些学习时间缩减策略.实现了进化学习的连续性和可扩展性,使得学习过程可以在40-60 min内完成,这样就能在比赛现场对ERS-7四足机器人进行行走再学习,提高了行走控制的适应性.算泫最终结果使ERS-7型四足机器人的行走速度从27 cm/s提升到43 cm/s.
By adopting evolution algorithm and autonomous-vision-based fitness evaluation approaches, the on-line automatic gait evolution of 4-legged robot in a RoboCup soccer field is realized. We incorporate interpolation method as the crossover method, use a PC base station to conduct algorithm calculation and flow control, and adopt some time-cutting strategies. The evolutionary learning is implemented with high continuity and expansibility, and the whole learning process can be completed within 40-60 minutes. In-field gait re-learning of the ERS-7 4-legged robot is realized, and the adaptability of walking control is improved. At last, the walking speed of ERS-7 4-legged robots is increased from 27 cm/s to 43 cm/s with the proposed algorithm.
出处
《机器人》
EI
CSCD
北大核心
2009年第1期72-76,81,共6页
Robot
基金
国家自然科学基金资助项目(60875057).
关键词
四腿机器人
步态学习
进化算法
行走控制
4-legged robot
gait learning
evolution algorithm
walking control
