【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.更多还原

【Abstract】 By adopting evolution algorithm and autonomous-vision-based fitness evaluation approaches,the on-line au- tomatic 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.更多还原