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      Reactive footstep planning for a planar spring mass hopper

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      Author
      Arslan, Ömür
      Saranlı, Uluç
      Morgül, Ömer
      Date
      2009-10
      Source Title
      IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
      Publisher
      IEEE
      Pages
      160 - 166
      Language
      English
      Type
      Conference Paper
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      Abstract
      The main driving force behind research on legged robots has always been their potential for high performance locomotion on rough terrain and the outdoors. Nevertheless, most existing control algorithms for such robots either make rigid assumptions about their environments (e.g flat ground), or rely on kinematic planning at low speeds. Moreover, the traditional separation of planning from control often has negative impact on the robustness of the system against model uncertainty and environment noise. In this paper, we introduce a new method for dynamic, fully reactive footstep planning for a simplified planar spring-mass hopper, a frequently used model for running behaviors. Our approach is based on a careful characterization of the model dynamics and an associated deadbeat controller, used within a sequential composition framework. This yields a purely reactive controller with a very large, nearly global domain of attraction that requires no explicit replanning during execution. Finally, we use a simplified hopper in simulation to illustrate the performance of the planner under different rough terrain scenarios and show that it is extremely robust to both model uncertainty and measurement noise. © 2009 IEEE.
      Keywords
      Control algorithms
      Driving forces
      Footstep planning
      Global domain
      Legged robots
      Low speed
      Measurement Noise
      Model dynamics
      Model uncertainties
      Negative impacts
      Re-planning
      Rough terrains
      Sequential compositions
      Spring mass
      Algorithms
      Controllers
      Hoppers
      Intelligent robots
      Landforms
      Planning
      Uncertainty analysis
      Robot programming
      Permalink
      http://hdl.handle.net/11693/28613
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/IROS.2009.5354354
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      • Department of Computer Engineering 1368
      • Department of Electrical and Electronics Engineering 3524
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