• Media type: Text; Doctoral Thesis; Electronic Thesis; E-Book
  • Title: Human-Inspired Balancing and Recovery Stepping for Humanoid Robots
  • Contributor: Kaul, Lukas Sebastian [Author]
  • Published: KIT-Bibliothek, Karlsruhe, 2019-01-01
  • Language: English
  • DOI: https://doi.org/10.5445/IR/1000092689
  • Keywords: Humanoid Robotics ; Optimal Control ; DATA processing & computer science ; Machine Learning
  • Origination:
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  • Description: Robustly maintaining balance on two legs is an important challenge for humanoid robots. The work presented in this book represents a contribution to this area. It investigates efficient methods for the decision-making from internal sensors about whether and where to step, several improvements to efficient whole-body postural balancing methods, and proposes and evaluates a novel method for efficient recovery step generation, leveraging human examples and simulation-based reinforcement learning.
  • Access State: Open Access