Vernaza, PaulLikhachev, MaximBhattacharya, SubhrajitKushleyev, AleksandrLee, Daniel DChitta, Sachin2023-05-222023-05-222009-05-122009-10-01https://repository.upenn.edu/handle/20.500.14332/34782We present a search-based planning approach for controlling a quadrupedal robot over rough terrain. Given a start and goal position, we consider the problem of generating a complete joint trajectory that will result in the legged robot successfully moving from the start to the goal. We decompose the problem into two main phases: an initial global planning phase, which results in a footstep trajectory; and an execution phase, which dynamically generates a joint trajectory to best execute the footstep trajectory. We show how R* search can be employed to generate high-quality global plans in the high-dimensional space of footstep trajectories. Results show that the global plans coupled with the joint controller result in a system robust enough to deal with a variety of terrains.legged locomotionpath planningposition controlcomplete joint trajectoryfootstep trajectorylegged robotrough terrainsearch-based planningsearch-based planning approachPresentation