MantisBot: A Platform for Investigating Mantis Behavior via Real-Time Neural Control

  • Nicholas S. Szczecinski
  • David M. Chrzanowski
  • David W. Cofer
  • David R. Moore
  • Andrea S. Terrasi
  • Joshua P. Martin
  • Roy E. Ritzmann
  • Roger D. Quinn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9222)


We present Mantisbot, a 28 degree of freedom robot controlled in real-time by a neural simulation. MantisBot was designed as a 13.3:1 model of a male Tenodera sinensis with the animal’s predominant degrees of freedom. The purpose of this robot is to investigate two main topics: 1. the control of targeted motion, such as prey-directed pivots and striking, and 2. the role of descending commands in transitioning between behaviors, such as standing, prey stalking, and walking. In order to more directly use data from the animal, the robot mimics its kinematics and range of motion as closely as possible, uses strain gages on its legs to measure femoral strain like insects, and is controlled by a realistic neural simulation of networks in the thoracic ganglia. This paper summarizes the mechanical, electrical, and software design of the robot, and how its neural control system generates reflexes observed in insects. It also presents preliminary results; the robot is capable of supporting its weight on four or six legs, and using sensory information for adaptive and corrective reflexes.


Real-time neural control Robot Mantis 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nicholas S. Szczecinski
    • 1
  • David M. Chrzanowski
    • 1
  • David W. Cofer
    • 1
  • David R. Moore
    • 1
  • Andrea S. Terrasi
    • 1
  • Joshua P. Martin
    • 1
  • Roy E. Ritzmann
    • 1
  • Roger D. Quinn
    • 1
  1. 1.Case Western Reserve UniversityClevelandUSA

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