ROBOT. Research and Implementation of Automatic Gait Evolution for 4-Legged Robot

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1 ROBOT Vol.31, No.1 Jan., (2009) RoboCup PC min ERS-7 ERS-7 27 cm/s 43 cm/s TP242.6 A Research and Implementation of Automatic Gait Evolution for 4-Legged Robot XU Tao CHEN Qi-jun (Department of Control Science and Engineering, Tongji University, Shanghai , China) Abstract: 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 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. Keywords: 4-legged robot; gait learning; evolution algorithm; walking control 1 Introduction [1] [2] Powell [3] [4] UNSW UTAustin RoboCup [5,6]

2 [7,8] 2 Aibo 4-legged robot Aibo and its locomotion model Aibo ERS-7 1 [9] double Fig.2 Locus of modified elliptical gait (the origin of coordinate is the geometrical center of the robot body) 1 3 Aibo ERS-7 Fig.1 The 4-legged robot Aibo ERS-7 with 3DOF for each leg 2 3 Walking gait evolution approaches

3 UNSW UTAustin 3.1 [70 mm,170 mm] Aibo [10] 3.2 r os r mut g i+1 = g i + θ rand a (1) g i g i+1 rand 0 1 θ a ( f,m) w 0 < w < 1 g i+1 = f i w + m i (1 w) + ( f i m i ) δ (2) g i+1 f i m i i δ 0 1 r c 3.3 RoboCup [11] RoboCup [12,13] 3 RoboCup Fig.3 A 4-legged robot evolves its walking gait in a RoboCup official field 3 4

4 cm/s PC 4 ERS7 IEEE802.11b LAN PC TCP/IP PC 20 min min PC PC n P(g) g P(g) = {x 1,x 2,,x n } Ft r os Begin g = 1 P(g) Ft(x i ) 1 While (running) Begin for each x i in P(g) if Ft(x i ) = 1 then Ft(x i ) Ft P(g) P(g) (1 r os ) n P(g + 1) g = g + 1 PC PC t S V m = S/t Fig.4 4 Evolution algorithm for 4-legged robot gait optimization 4 Experimental results and analysis 43 cm/s 5 1

5 RoboCup 1 Tab.1 Gait evolution control parameters in the experiment N 10 r os 0.5 r mut 0.05 a 0.2 r c Conclusion (a) (b) 5 Fig.5 Experiment result of 4-legged robot gait evolution Aibo ERS-7 43 cm/s 27 cm/s 59.3% min TJArk 2007 RoboCup 6 Acknowledgment TJArk TJArk 81

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