Optimizing energy consumption and preventing slips at the footstep planning level

Energy consumption and stability are two important problems for humanoid robots deployed in remote outdoor locations. In this paper we propose an extended footstep planning method to optimize energy consumption while considering motion feasibility and ground friction constraints. To do this we estimate models of energy, feasibility and slippage in physics simulation, and integrate them into a hybrid A∗ search and optimization-based planner. The graph search is done in footstep position space, while timing (leg swing and double support times) and COM motion (parameterized height trajectory) are obtained by solving an optimization problem at each node. We conducted experiments to validate the obtained energy model on the real robot, as well as planning experiments showing 9 to 19% energy savings. In example scenarios, the robot can correctly plan to optimally traverse slippery patches or avoid them depending on their size and friction; and uses stairs with the most beneficial dimensions in terms of energy consumption.