Genetic algorithm for control design of biped locomotion

Dynamic biped walking is a difficult control problem. The design involves that of the controller as well as the gait. A typical design procedure involves tedious analysis, careful planning, and testing. The procedure is time consuming and the analysis is often based on some linearized model. Selection of control parameters and nominal trajectory determines the quality of control and in typical designs, some or all of the parameters are selected intuitively. The result is often not the best. If some special goal (such as to walk as fast as possible) is desirable, the design may become even harder. While the analytical approach is not easy, one possible alternative is to obtain the optimal or near-optimal design through parameter search. This study explores this approach. The design of the biped controller and gait is formulated as a parameter search problem, and a genetic algorithm is applied to help obtain the optimal design. Designs to achieve different goals, such as being able to walk on an inclined surface, walk at a high speed, or walk with a specified step size have been evolved with the use of the genetic algorithm. Simulation results show that the genetic algorithm (GA) is capable of finding good solutions. (C) 1997 John Wiley & Sons, Inc.