Impact Force Reduction Using Variable Stiffness with an Optimal Approach for Falling Robots

  • Juan Calderon
  • Gustavo A. Cardona
  • Martin Llofriu
  • Muhaimen Shamsi
  • Fallon Williams
  • Wilfrido Moreno
  • Alfredo Weitzenfeld
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)

Abstract

The work described in this paper is focused on the reduction of the impact force exerted by the ground on a falling humanoid robot. It proposes the use of a variable stiffness in the arms’s motors to prevent damages. The proposed work is applicable when the falling prevention techniques fail or when falling is unavoidable. This work proposes the generation of variable stiffness in a motor through the optimal design of a PID controller. The variation of the Q matrix in a LQR controller produces different levels of motor stiffness. The proposed variable stiffness is tested in a Darwin OP Robot. The performance of the proposed design is evaluated using the estimation of the impact force. Results show an impact force reduction on falling motions by means of stiffness variation.

Keywords

Variable stiffness Optimal control Humanoid robot Falling robot 

Notes

Acknowledgments

This work is supported in part at USF by NSF-CRCNS grant #1429937, “A replay-driven model of spatial sequence learning in the Hippocampus-PFC network using reservoir computing”.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Juan Calderon
    • 1
    • 3
  • Gustavo A. Cardona
    • 4
  • Martin Llofriu
    • 2
  • Muhaimen Shamsi
    • 2
  • Fallon Williams
    • 2
  • Wilfrido Moreno
    • 1
  • Alfredo Weitzenfeld
    • 2
  1. 1.Department of Electrical EngineeringUniversity of South FloridaTampaUSA
  2. 2.Department of Computer Science and EngineeringUniversity of South FloridaTampaUSA
  3. 3.Department of Electronic EngineeringUniversidad Santo TomásBogotaColombia
  4. 4.Department of Electrical and Electronics EngineeringUniversidad Nacional de ColombiaBogotaColombia

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