Abstract. This paper presents a new approach to optimize gait parameter sets using evolutionary algorithms. It separates the crossover-step of the evolutionary algorithm into an in...
Given the complexity of the problem, genetic algorithms are one of the more promising methods of discovering control schemes for soft robotics. Since physically embodied evolution...
John Rieffel, Frank Saunders, Shilpa Nadimpalli, H...
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function opt...
Daniel J. Lizotte, Tao Wang, Michael H. Bowling, D...
We propose an approach of automated co-evolution of the optimal values of attributes of active sensing (orientation, range and timing of activation of sensors) and the control of ...
In this paper an evolutionary algorithm is used for evolving gaits in a walking biped robot controller. The focus is fast learning in a real-time environment. An incremental appro...