期刊
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
卷 30, 期 2, 页码 175-191出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0278364910392608
关键词
Legged robots; motion control; adaptive control; nonholonomic motion planning; mobile robotics
类别
资金
- DARPA
- Div Of Electrical, Commun & Cyber Sys
- Directorate For Engineering [0824077] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0964581] Funding Source: National Science Foundation
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to plan a set of footholds, along with the dynamic body motions required to execute them. Components within the planning framework coordinate to exchange plans, cost-to-go estimates, and 'certificates' that ensure the output of an abstract high-level planner can be realized by lower layers of the hierarchy. The burden of careful engineering of cost functions to achieve desired performance is substantially mitigated by a simple inverse optimal control technique. Robustness is achieved by real-time re-planning of the full trajectory, augmented by reflexes and feedback control. We demonstrate the successful application of our approach in guiding the LittleDog quadruped robot over a variety of types of rough terrain. Other novel aspects of our past research efforts include a variety of pioneering inverse optimal control techniques as well as a system for planning using arbitrary pre-recorded robot behavior.
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