Gait Synthesis for Legged Underwater Vehicles

Legged autonomous vehicles move by executing patterns of leg-joint angles known as gaits. Synthesizing gaits by hand is a complex and time-consuming task which becomes even more challenging when the vehicle operates underwater. When operating underwater any motion of the limbs applies forces to the vehicle. Underwater gaits must therefore be constructed to mitigate these unwanted forces while meeting the desired gait properties. This paper presents an automatic gait synthesis system for underwater legged vehicles. The system utilizes a simulated annealing engine coupled with a black box hydrodynamic vehicle model to synthesize the desired gait. The resulting system is used to synthesize gaits for a simulated version of the AQUA amphibious hexapod although it is general enough to be applied to other legged vehicles.

[1]  Kenneth J. Waldron,et al.  Machines That Walk: The Adaptive Suspension Vehicle , 1988 .

[2]  Andrew Hogue,et al.  AQUA: An Amphibious Autonomous Robot , 2007, Computer.

[3]  Kazuo Tsuchiya,et al.  A study on optimal gait pattern of a quadruped locomotion robot , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[4]  Changjiu Zhou,et al.  Humanoid Walking Gait Optimization Using GA-Based Neural Network , 2005, ICNC.

[5]  Downloaded from , 1997 .

[6]  Full,et al.  Underwater punting by an intertidal crab: a novel gait revealed by the kinematics of pedestrian locomotion in air versus water , 1998, The Journal of experimental biology.

[7]  George A. Bekey,et al.  Genetic Algorithms for Gait Synthesis in a Hexapod Robot , 1994 .

[8]  Juan C. Grieco,et al.  Gait Synthesis and Modulation for Quadruped Robot Locomotion Using a Simple Feed-Forward Network , 2006, ICAISC.

[9]  Jih-Gau Juang,et al.  Fuzzy neural network approaches for robotic gait synthesis , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[10]  Andrew Hogue,et al.  AQUA: an aquatic walking robot , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[11]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.