Biological Cybernetics

, Volume 112, Issue 1–2, pp 99–112 | Cite as

Leg-local neural mechanisms for searching and learning enhance robotic locomotion

  • Nicholas S. Szczecinski
  • Roger D. Quinn
Original Article


Adapting motor output based on environmental forces is critical for successful locomotion in the real world. Arthropods use at least two neural mechanisms to adjust muscle activation while walking based on detected forces. Mechanism 1 uses negative feedback of leg depressor force to ensure that each stance leg supports an appropriate amount of the body’s weight. Mechanism 2 encourages searching for ground contact if the leg supports no body weight. We expand the neural controller for MantisBot, a robot based upon a praying mantis, to include these mechanisms by incorporating leg-local memory and command neurons, as observed in arthropods. We present results from MantisBot transitioning between searching and stepping, mimicking data from animals as reported in the literature.


Synthetic nervous system Central pattern generator Sensory feedback Locomotion Stability Robotics 


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.ClevelandUSA

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