Skip to main content
Log in

An adaptive locomotion controller for a hexapod robot: CPG, kinematics and force feedback

  • Research Paper
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

Insects can perform versatile locomotion behaviors such as multiple gaits, adapting to different terrains, fast escaping, etc. However, most of the existing bio-inspired legged robots do not possess such walking ability, especially when they walk on irregular terrains. To tackle this challenge, a central pattern generator (CPG)-based locomotion control methodology is proposed, integrated with a contact force feedback function. In this approach, multiple gaits are produced by the CPG module. After passing through a post-processing circuit and a delay-line, the control signal is fed into six trajectory generators to generate predefined feet trajectories for the six legs. Then, force feedback is employed to adjust these trajectories so as to adapt the robot to rough terrains. Finally the regulated trajectories are sent to inverse kinematics modules such that the position control instructions are generated to control the actuators. In both simulations and real robot experiments, we consistently show that the robot can perform sophisticated walking patterns. What is more, the robot can use the force feedback mechanism to deal with the irregularity in rough terrain. With this mechanism, the stability and adaptability of the robot are enhanced. In conclusion, the CPG-base control is an effective approach for legged robots and the force feedback approach is able to improve walking ability of the robots, especially when they walk on irregular terrains.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Wilson D. Insect walking. Ann Rev Entom, 1966, 11: 103–122

    Article  Google Scholar 

  2. Kingsley D. A cockroach inspired robot with artificial muscles. Ph.D. Thesis. Case Western Reserve University, 2005

    Google Scholar 

  3. Ho T, Lee S. A fast mesoscale quadruped robot using piezocomposite actuators. Robotica, 2013, 31: 1–10

    Article  Google Scholar 

  4. Quinn R, Offi J, Kingsley D, et al. Improved mobility through abstracted biological principles. In: Proceedings of 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, 2002. 2652–2657

    Google Scholar 

  5. Ferrell C. A comparison of three insect-inspired locomotion controllers. Robotics Auton Syst, 1995, 16: 135–159

    Article  Google Scholar 

  6. Buehler M, Playter R, Raibert M. Robots step outside. In: International Symposium on Adaptive Motion of Animals and Machines, Ilmenau, 2005. 1–4

    Google Scholar 

  7. Kalakrishnan M, Buchli J, Pastor P, et al. Fast, robust quadruped locomotion over challenging terrain. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Alaska, 2010. 2665–2670

    Chapter  Google Scholar 

  8. Zucker M, Bagnell J, Atkeson C, et al. An optimization approach to rough terrain locomotion. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA2010), Alaska, 2010. 3589–3595

    Chapter  Google Scholar 

  9. Go Y, Yin X, Bowling A. Navigability of multi-legged robots. IEEE/ASME Trans Mechatr, 2006, 11: 1–8

    Article  Google Scholar 

  10. Bai S, Low K, Teo M. Path generation of walking machines in 3D terrain. In: Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington, 2002. 2216–2221

    Google Scholar 

  11. Silva M, Machado J. Kinematic and dynamic performance analysis of aitificial legged systems. Robotica, 2008, 26: 19–39

    Article  Google Scholar 

  12. Dickinson M, Farley C, Full R, et al. How animals move: An integrative view. Science, 2000, 288: 100–106

    Article  Google Scholar 

  13. Bläsing B, Cruse H. Stick insect locomotion in a complex environment: Climbing over large gaps. J Exper Biol, 2004, 207: 1273–1286

    Article  Google Scholar 

  14. Schilling M, Cruse H, Arena P. Hexapod walking: An expansion to walknet dealing with leg amputations and force oscillations. Biol Cybern, 2007, 96: 323–340

    Article  MATH  Google Scholar 

  15. Cruse H, Dürr V, Schilling M, et al. Principles of insect locomotion. In: Arena P, Patané L, eds. Spatial Temporal Patterns for Action-Oriented Perception in Roving Robots. Springer, 2009. 43–96

    Chapter  Google Scholar 

  16. Cruse H, Dürr V, Schmitz J. A bottom-up approach for cognitive control. In: Arena P, Patané L, eds. Spatial Temporal Patterns for Action-Oriented Perception in Roving Robots. Springer, 2009. 179

    Chapter  Google Scholar 

  17. Delcomyn F. Walking robots and the central and peripheral control of locomotion in insects. Auton Robots, 1999, 7: 259–270

    Article  Google Scholar 

  18. Taga G, Yamaguchi Y, Shimizu H. Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment. Biol Cybern, 1991, 65: 147–159

    Article  MATH  Google Scholar 

  19. Aoi S, Egi Y, Sugimoto R, et al. Functional roles of phase resetting in the gait transition of a biped robot from quadrupedal to bipedal locomotion. IEEE Trans Robotics, 2012, 28: 1–16

    Article  Google Scholar 

  20. Kimura H, Fukuoka Y, Cohen A. Adaptive dynamic walking of a quadruped robot on natural ground based on biological concepts. Inter J Robotics Res, 2007, 26: 475–490

    Article  Google Scholar 

  21. Zhang X, Zheng H. Walking up and down hill with a biologically-inspired postural reflex in a quadrupedal robot. Auton Robots, 2008, 25: 15–24

    Article  Google Scholar 

  22. Zhang X, Zheng H. Autonomously clearing obstacles using the biological flexor reflex in a quadrupedal robot. Robotica, 2008, 26: 1–7

    Article  MATH  Google Scholar 

  23. Arena P, Fortuna L, Frasca M, et al. An adaptive, self-organizing dynamical system for hierarchical control of bioinspired locomotion. IEEE Trans Syst Man Cybern, Part B: Cybernetics, 2004, 34: 1823–1837

    Article  Google Scholar 

  24. Inagaki S, Yuasa H, Suzuki T, et al. Wave CPG model for autonomous decentralized multi-legged robot: Gait generation and walking speed control. Robotics Auton Syst, 2006, 54: 118–126

    Article  Google Scholar 

  25. Manoonpong P, Pasemann F, Wörgötter F. Sensor-driven neural control for omnidirectional locomotion and versatile reactive behaviors of walking machines. Robotics Auton Syst, 2008, 56: 265–288

    Article  Google Scholar 

  26. Steingrube S, Timme M, Wörgötter F, et al. Self-organized adaptation of a simple neural circuit enables complex robot behaviour. Nature Phys, 2010, 6: 224–230

    Article  Google Scholar 

  27. Ijspeert A, Crespi A, Ryczko D, et al. From swimming to walking with a salamander robot driven by a spinal cord model. Science, 2007, 315: 1416–1420

    Article  Google Scholar 

  28. Crespi A, Ijspeert A. Online optimization of swimming and crawling in an amphibious snake robot. IEEE Trans Robotics, 2008, 24: 75–87

    Article  Google Scholar 

  29. Wu X, Ma S. Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change. Auton Robots, 2010, 28: 283–294

    Article  Google Scholar 

  30. Wu Z, Yu J, Tan M. CPG parameter search for a biomimetic robotic fish based on particle swarm optimization. In: Proceedings of 2012 IEEE International Conference on Robotics and Biomimetics, Guangzhou, 2012. 563–568

    Chapter  Google Scholar 

  31. Yu J, Wei C. Towards development of a slider-crank centered self-propelled dolphin robot. Adv Robotics, 2013, 27: 1–7

    Article  Google Scholar 

  32. Ijspeert A. Central pattern generators for locomotion control in animals and robots: A review. Neural Networks, 2008, 21: 642–653

    Article  Google Scholar 

  33. Ren G, Chen W, Kolodziejski C, et al. Multiple chaotic central pattern generators for locomotion generation and leg damage compensation in a hexapod robot. In: Proceedings of 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, 2012. 2756–2761

    Chapter  Google Scholar 

  34. Chen W, Ren G, Zhang J, et al. Smooth transition between different gaits of a hexapod robot via a central pattern generators algorithm. J Intell Robotic Syst, 2012, 67: 255–270

    Article  MATH  Google Scholar 

  35. Buchli J, Righetti L, Ijspeert A. Engineering entrainment and adaptation in limit cycle systems. Biol Cybern, 2006, 95: 645–664

    Article  MathSciNet  MATH  Google Scholar 

  36. Bai S, Low K, Zielinska T. Quadruped free gait generation based on the primary/secondary gait. Robotica, 1999, 17: 405–412

    Article  Google Scholar 

  37. Ugurlu B, Kawasaki T, Kawanishi M, et al. Continuous and dynamically equilibrated one-legged running experiments: Motion generation and indirect force feedback control. In: Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, 2012. 1846–1852

    Chapter  Google Scholar 

  38. Boaventura T, Focchi M, Frigerio M, et al. On the role of load motion compensation in high-performance force control. In: Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, 2012. 4066–4071

    Chapter  Google Scholar 

  39. Li Y, Ahmed A, Sameoto D, et al. Abigaille II: Toward the development of a spider-inspired climbing robot. Robotica, 2012, 30: 79–89

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to WeiHai Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, W., Ren, G., Wang, J. et al. An adaptive locomotion controller for a hexapod robot: CPG, kinematics and force feedback. Sci. China Inf. Sci. 57, 1–18 (2014). https://doi.org/10.1007/s11432-014-5148-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-014-5148-y

Keywords

Navigation