Search-based planning for a legged robot over rough terrain

Abstract

: 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 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 pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Search-based Planning for a Legged Robot over Rough Terrain AbstractWe 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. 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 pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Abstract-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 highdimensional 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. ...

Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots

“…This can cause the robot to locally navigate into an unsurmountable obstacle. To avoid this, some controllers [15], [13] globally plan the complete footsteps from start to goal, though in this case time consuming replanning is necessary in case of slippage or deviation from the planned path. The approach in [12] stands between the two above mentioned methods and plans a global rough body path to avoid local minima, but the specific footholds are chosen only a few steps in advance.…”

Onboard perception-based trotting and crawling with the Hydraulic Quadruped Robot (HyQ)

“…The teams involved in this competition produced similar planning and control solutions [10], [11], [12]. All teams built upon a global plan over sets of given maps, while footholds were selected with hand-tuned, and learnt, features of varying terrain area resolution.…”

“…This problem has been the focus of much research work resulting in a variety of generally cost based approaches [10], [12]. Most of such approaches assume accurate and global knowledge of the locomotion surface and often millimeter-accurate localization from an external source, typically a motion capture system.…”

Disturbance detection, identification, and recovery by gait transition in legged robots

“…To date most of the locomotion literature has addressed operation in the extremes: either fixed, consistent terrain wherein a specific gait can be tuned over repeated trials and accumulating experience [2,[4][5][6][7][8] or wildly varied footing conditions [9][10][11][12] wherein it is not at all clear that the notion of a gait is even appropriate. We are aware of only two investigations of adaptive legged locomotion in the presumably far more common middleground setting of challenging but "modestly" varying terrain: on-line deterministic gait parameter feedback [13]; and tuned robustness against stochastic perturbation of an open loop stride-map as an alternative to deterministic gaits [14].…”