Thinning and smoothing of randomly-sampled support transitions toward practical motion planning for humanoid robots

A motion planning method for humanoid robots in life environments is proposed based on a two-stage approach, where a sequence of double support postures to represent discrete milestones of the biped locomotion is planned first, and then, a time series of the whole body configuration to interpolate them. This paper discusses the first stage. RRT (Rapidly-explored Random Tree) is utilized for the planning. The main problem is how to modify the sequence of randomly sampled double support postures into practically acceptable one. Some post-processing techniques including thinning and smoothing are presented. A necessary condition of the series of milestones is that a pair of adjacent postures has to share one fixed supporting foot as the pivot. In order to thin out unnecessary milestones, bypass nodes are inserted and Dijkstra´s method is applied. A computer simulation in which a humanoid robot travels in an environment with some pieces of furniture is demonstrated.