Linear reactive control for efficient 2D and 3D bipedal walking over rough terrain

Joseph H. Solomon, Mark A. Locascio, Mitra J Z Hartmann

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The kinematics of human walking are largely driven by passive dynamics, but adaptation to varying terrain conditions and responses to perturbations require some form of active control. The basis for this control is often thought to take the form of entrainment between a neural oscillator (i.e., a central pattern generator and/or distributed counterparts) and the mechanical system. Here we use techniques in evolutionary robotics to explore the potential of a purely reactive, linear controller to control bipedal locomotion over rough terrain. In these simulation studies, joint torques are computed as weighted linear sums of sensor states, and the weights are optimized using an evolutionary algorithm. We show that linear reactive control can enable a seven-link 2D biped and a nine-link 3D biped to walk over rough terrain (steps of ~5% leg length or more in the 2D case). In other words, the simulated walker gradually learns the appropriate weights to achieve stable locomotion. The results indicate that oscillatory neural structures are not necessarily a requirement for robust bipedal walking. The study of purely reactive control through linear feedback may help to reveal some basic control principles of stable walking.

Original languageEnglish (US)
Pages (from-to)29-46
Number of pages18
JournalAdaptive Behavior
Volume21
Issue number1
DOIs
StatePublished - Feb 2013

Funding

We would like to express our special thanks to Dr. Shoushi, Mr. Zadeh Dabbagh and Mr. Yavari for helping with this research.

Keywords

  • Bipedal walking
  • biped
  • dynamic walking
  • evolutionary robotics
  • reactive control
  • rough terrain

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Behavioral Neuroscience

Fingerprint

Dive into the research topics of 'Linear reactive control for efficient 2D and 3D bipedal walking over rough terrain'. Together they form a unique fingerprint.

Cite this