Event Abstract

Reactive Neural Climbing Control for Hexapod Robots

  • 1 Georg-August-Universität Göttingen, Bernstein Center for Computational Neuroscience, Germany
  • 2 Georg-August-Universität Göttingen, Bernstein Focus Neurotechnology, Germany

Insects, e.g. cockroaches, have found fascinating solutions for the problem of locomotion, in particular climbing over a large variety of obstacles. Neuroethological study has identified key behavioral patterns of these animals necessary for climbing: body flexion [1], center of mass (CoM) elevation [2], and local leg reflexes [3]. For example, when cockroaches start to climb over an obstacle they extend their middle legs to push the front body from the ground (CoM elevation). Afterwards, they tilt the prothorax down (i.e., body flexion) to support their locomotion and keep balance during climbing. In other situations, like locomotion through complex landscapes, there is a high probability for legs to get stuck. Searching and elevator reflexes tend to solve such problems leading to effective locomotion including climbing over obstacles.

Inspired by this finding, we develop reactive climbing control for our hexapod robot AMOS II. The controller is composed of three main neural circuits: neural locomotion control, neural reactive backbone joint control, and neural local leg reflex control. The locomotion control generates basic walking behavior including omnidirectional walking and different gaits of the robot. The reactive backbone joint control supports the climbing behavior of the robot by emulating the body flexion observed in cockroaches. The local leg reflex control activates searching and elevator reflexes as well as CoM elevation.

The controller was developed and successfully tested using our modular robot control environment, allowing physical simulation and simple transferring to AMOS II. Experimental results show that the developed reactive climbing control allows the robot to surmount obstacles with a maximum height of 13 cm which equals 75% of its leg length (see supplementary video at http://www.manoonpong.com/BCCN2012/ReactiveClimbing.wmv). As a comparison, a quadruped robot presented in [4] successfully negotiated obstacles up to 40% of its leg length while the hexapod Gregor I [5] and the octopod Scorpion IV [6] achieved a height of 65% and 55% of its leg length, respectively. In addition, AMOS II displays the three key behavior patterns found in neuroethological studies. Therefore, the experiments not only show that AMOS II exhibits outstanding climbing capabilities, but its control system also generates climbing behavior similar to the behavior observed in insects.


This research was supported by Emmy Noether grant MA4464/3-1 of the Deutsche Forschungsgemeinschaft (DFG), the Bernstein Center for Computational Neuroscience II Göttingen (BCCN II grant 01GQ1005A, project D1), and the Bernstein Focus Neurotechnology Göttingen (BFNT project 3B, 01GQ0811).


[1] R. Ritzmann, R. Quinn, and M. Fischer, “Convergent evolution and locomotion through complex terrain by insects, vertebrates and robots,” Arthropod Structure & Development, vol. 33, no. 3, pp. 361–379, 2004.
[2] J. T. Watson, R. E. Ritzmann, S. N. Zill, and A. J. Pollack, “Control of obstacle climbing in the cockroach, blaberus discoidalis: I. locomotion,” J Comp Physiol, vol. 188, no. 1, pp. 39–53, 2002.
[3] H. Fischer, J. Schmidt, R. Haas, and A. Büschges, “Pattern generation for walking and searching movements of a stick insect leg. I. coordination of motor activity,” Journal of neurophysiology, vol. 85, no. 1, pp. 341-53, 2001.
[4] H. Lee, Y. Shen, C.-H. Yu, G. Singh, and A. Y. Ng, “Quadruped robot obstacle negotiation via reinforcement learning,” IEEE International Conference on Robotics and Automation, 2006.
[5] M. Pavone, P. Arena, L. Fortuna, M. Frasca, and L. Patane, “Climbing obstacle in bio-robots via CNN and adaptive attitude control,” International journal of circuit theory and applications, vol. 34, no. 1, pp.109–125, 2006.
[6] B. Klaassen, R. Linnemann, D. Spenneberg, and F. Kirchner, “Biomimetic walking robot SCORPION: control and modeling,” Robotics and Autonomous Systems, vol. 41, no. 2-3, pp. 69–76, 2002.

Keywords: Autonomous legged robots, Leg reflexes, Locomotion control, neural networks, Obstacle climbing

Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012.

Presentation Type: Poster

Topic: Motor control, movement, navigation

Citation: Goldschmidt D, Hesse F, Wörgötter F and Manoonpong P (2012). Reactive Neural Climbing Control for Hexapod Robots. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00220

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Received: 10 May 2012; Published Online: 12 Sep 2012.

* Correspondence: Dr. Poramate Manoonpong, Georg-August-Universität Göttingen, Bernstein Center for Computational Neuroscience, Göttingen, 37077, Germany, poma@mmmi.sdu.dk