Search-based Planning for a Legged Robot over Rough Terrain

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Lab Papers (GRASP)
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legged locomotion
path planning
position control
complete joint trajectory
footstep trajectory
legged robot
rough terrain
search-based planning
search-based planning approach
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We 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.

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Copyright 2009 IEEE. Reprinted from: Vernaza, P.; Likhachev, M.; Bhattacharya, S.; Chitta, S.; Kushleyev, A.; Lee, D.D., "Search-based planning for a legged robot over rough terrain," Robotics and Automation, 2009. ICRA '09. IEEE International Conference on , vol., no., pp.2380-2387, 12-17 May 2009 URL: This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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