Fast Kinodynamic Bipedal Locomotion Planning with Moving Obstacles

Abstract

In this paper, we present a sampling-based kino-dynamic planning framework for a bipedal robot in complex environments. Unlike other footstep planning algorithms which typically plan footstep locations and the biped dynamics in separate steps, we handle both simultaneously. Three primary advantages of this approach are (1) the ability to differentiate alternate routes while selecting footstep locations based on the temporal duration of the route as determined by the Linear Inverted Pendulum Model (LIPM) dynamics, (2) the ability to perform collision checking through time so that collisions with moving obstacles are prevented without avoiding their entire trajectory, and (3) the ability to specify a minimum forward velocity for the biped. To generate a dynamically consistent description of the walking behavior, we exploit the Phase Space Planner (PSP) [1] [2]. To plan a collision-free route toward the goal, we adapt planning strategies from non-holonomic wheeled robots to gather a sequence of inputs for the PSP. This allows us to efficiently approximate dynamic and kinematic constraints on bipedal motion, to apply a sampling-based planning algorithm such as RRT or RRT*, and to use the Dubin's path [3] as the steering method to connect two points in the configuration space. The results of the algorithm are sent to a Whole Body Controller [1] to generate full body dynamic walking behavior. Our planning algorithm is tested in a 3D physics-based simulation of the humanoid robot Valkyrie.