TY - GEN
T1 - Energetically optimal gait transition velocities of a quadruped robot
AU - Shmuel, Iris
AU - Riemer, Raziel
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Determining gait patterns with low energy consumption per distance traveled are important for increasing robots operation range. These gait patterns, a function of the robot's speed and structure, are generally determined by optimization processes. In contrast to previous studies that examined the energy consumption of several gait patterns at specific travel velocities, this study presents an optimization process that determines the optimal gait pattern for a range of velocities. In the first part of the study, three optimization methods are compared - The genetic algorithm, the radial-basis function method and the Nelder-Mead simplex. Results indicated that the preferred optimization method is genetic algorithm. In the second part of the study, we reduced the number of optimization variables, using constraints that represent known gait patterns. This led to a reduction of approximately 50% in optimization runtime, while maintaining similar energy consumption per distance as achieved in the first part of the study.
AB - Determining gait patterns with low energy consumption per distance traveled are important for increasing robots operation range. These gait patterns, a function of the robot's speed and structure, are generally determined by optimization processes. In contrast to previous studies that examined the energy consumption of several gait patterns at specific travel velocities, this study presents an optimization process that determines the optimal gait pattern for a range of velocities. In the first part of the study, three optimization methods are compared - The genetic algorithm, the radial-basis function method and the Nelder-Mead simplex. Results indicated that the preferred optimization method is genetic algorithm. In the second part of the study, we reduced the number of optimization variables, using constraints that represent known gait patterns. This led to a reduction of approximately 50% in optimization runtime, while maintaining similar energy consumption per distance as achieved in the first part of the study.
KW - Dynamic gait
KW - Energetic consumption
KW - Gait transition
KW - Genetic algorithm
KW - Optimization
KW - Quadruped robot
UR - https://www.scopus.com/pages/publications/84893565085
U2 - 10.1109/SMC.2013.469
DO - 10.1109/SMC.2013.469
M3 - Conference contribution
SN - 9780769551548
T3 - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
SP - 2747
EP - 2752
BT - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
T2 - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Y2 - 13 October 2013 through 16 October 2013
ER -