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To increase the speed of operation and reduce operator burden, humanoidrobots must be able to function autonomously, even in complex, clutteredenvironments. For this to be possible, they must be able to quickly andefficiently compute desired footsteps to reach a goal. In this work, we presenta new A* footstep planner that utilizes a planar region representation of theenvironment enable footstep planning over rough terrain. To increase the numberof available footholds, we present an approach to allow the use of partialfootholds during the planning process. The footstep plan solutions are thenpost-processed to capture better solutions that lie between the latticediscretization of the footstep graph. We then demonstrate this planner over avariety of virtual and real world environments, including some that requirepartial footholds and rough terrain using the Atlas and Valkyrie humanoidrobots.

Footstep Planning for Autonomous Walking Over Rough Terrain