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Analytical and Experimental Investigations of Feedback Control Designs for Bipedal Walkers and Runners

Analytical and Experimental Investigations of Feedback Control Designs for Bipedal Walkers and Runners
双足步行者和跑步者反馈控制设计的分析和实验研究
批准号:
0856213
负责人:
Jessy Grizzle
金额:
$46.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-15 至 2014-07-31

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中文摘要
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英文摘要
Objective: The objective of this research program is to develop systematic, model-based feedback design procedures for a class of bipedal robots that take advantage of compliance in order to enhance locomotion efficiency and robustness when running on smooth terrain and walking on rough terrain. Intellectual Merit: It is estimated that 70% of the earth's landmass is inaccessible to wheeled or tracked vehicles. With legs, robots can step over obstacles or use sparse footholds. Bipedal robots are complex, hybrid systems. The associated feedback control algorithms that realize and stabilize these motions must be hybrid as well. This research thus contributes very concretely to the general theory of hybrid systems. The ability of the theory to tolerate model imperfections will be evaluated in the laboratory on an bipedal robot named MABEL. The successful operation of this innovative machine requires equally innovative feedback control theory that works in concert with the natural dynamics of the system to achieve stability and robustness of the implemented behaviors.This project has the potential to transform our ability to design, build and control robots that are capable of realizing locomotion behaviors that are more agile and human-like than ever before. Broader Impacts: Research on bipedal robotic locomotion can improve prosthesis design and lower-limb rehabilitation robotics. The anthropomorphic nature of bipedal robots makes them a wonderful vehicle for motivating very challenging problems in engineering, without having to assume familiarity with advanced mathematics or physics. Professor Grizzle gives presentations on his research results to lay groups, including high schools, junior high and grade school science camps, civic organizations, retirees and the like, and organizes field trips to see feedback control in action on his bipedal robot, MABEL.
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会议论文
Learning-Aided Integrated Control and Semantic Perception Architecture for Legged Robot Locomotion and Navigation in the Wild
Combining Optimization, Machine Learning, and Model Structure to Improve the Robustness and Agility of Modern Bipedal Machines
NRI: Collaborative Research: Unified Feedback Control and Mechanical Design for Robotic, Prosthetic, and Exoskeleton Locomotion
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