Kinematics, Navigation, and Path Planning of Hexapod Robot

  • Kenzo Nonami
  • Ranjit Kumar Barai
  • Addie Irawan
  • Mohd Razali Daud
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 66)


In Chap. 3, fundamental analysis on COMET-IV’s leg kinematics and dynamics has been briefly discussed. On further research progress on this robot, the developed kinematics and dynamics are exploited to be used for end-effector force on foot detection and overall COMET-IV stability for force-attitude control purposes. In COMET-IV research progress, the total force on foot is calculated for center of mass (CoM) identification as an input for robot attitude during walking session. This method is based on shoulder coordination system (SCS) kinematics on vertical position and total of force on foot for each touching leg on the ground. On the other hand, the designed force delivery on foot value is categorized phase by phase and threshold sensing method is applied for dynamic trajectory walking named force threshold-based trajectory. This method is done to achieve the novel end-effector force sensorless method that is applicable for large-scale legged robot that required expensive sensor on each leg’s tip.


Global Position System Zero Moment Point Legged Robot Uneven Terrain Hexapod Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Oku M, Yang H, Paio G, Harada Y, Adachi K, Barai R, Sakai S, Nonami K (2007) Development of hydraulically actuated hexapod robot COMET-IV – The 1st report: system design and configuration. In: Proceeding of JSME conference on robotics and mechatronics 2007 (ROBOMEC 2007), Akita, pp 2A2–G01Google Scholar
  2. 2.
    Ohroku H, Irawan A, Nonami K (2009) A 3D modeling for hydraulic-drive hexapod walking robot using 3D geometric technique with distributed numerical model. Int J Automat Robot Auton Syst 9(1)Google Scholar
  3. 3.
    Oku M, Koseki H, Ohroku H, Harada Y, Futagami K, Tran DC, Li L, Lin X, Sakai S, Nonami K (2008) Rough terrain locomotion control of hydraulically actuated hexapod robot COMET-IV (in Japanese). In: JSME conference on robotics and mechatronics 2008 (ROBOMEC 2008), NaganoGoogle Scholar
  4. 4.
    Aoyama H, Goto M, Naruo A, Hamada K, Kikuchi N, Kojima Y, Takada Y, Takenaka Y (2006) The difference between center of mass and center of pressure: a review of human postural control. Aino J 5Google Scholar
  5. 5.
    Byl K (2008) Metastable legged-robot locomotion. Massachusetts Institute of Technology, CambridgeGoogle Scholar
  6. 6.
    Schleicher D, Bergasa LM (2009) Real-time hierarchical outdoor SLAM based on stereovision and GPS fusion. IEEE Trans Intell Transport Syst 10(3):440–452CrossRefGoogle Scholar
  7. 7.
    Ishikawa K, Amano Y, Hashizume T (2007) A mobile mapping system for precise road line localization using a single camera and 3D road model. J Robot Mech 19(2):174–180Google Scholar
  8. 8.
    Sakai A, Saitoh T, Kuroda Y (2010) Robust landmark estimation and unscented particle sampling for SLAM in dynamic outdoor environment. J Robot Mech 22(2):140–149Google Scholar
  9. 9.
    Chang HJ, George Lee CS, Lu YH, Hu YC (2007) P-SLAM: simultaneous localization and mapping with environmental-structure prediction. IEEE Trans Robot 23(2):281–293CrossRefGoogle Scholar
  10. 10.
    Hodoshima R, Doi T, Fukuda Y, Hirose S, Okamoto T, Mori J (2007) Development of a quadruped walking robot TITAN XI for steep slope operation – step over gait to avoid concrete frames on steep slopes. J Robot Mech 19(1)Google Scholar
  11. 11.
    Nabulasi S, Armada MA, Montes H (2006) Multiple terrain adaptation approach using ultrasonic sensors for legged robots. In: Proceeding of climbing and walking robots 2006 (CLAWAR 2006), BrusselsGoogle Scholar
  12. 12.
    Raibert M, Blankespoor K, Nelson G, Playter R (2008) TheBigDogTeam BigDog: the rough terrain quadruped robot. In: Proceeding of 17th world congress, the international federation of automatic control, SeoulGoogle Scholar
  13. 13.
    Murata T, Yamaguchi M (2008) Multi-legged robot control using GA-based Q-learning method with neighboring crossover. In: Iba H (ed) Frontiers in evolutionary robotics. I-Tech Education and Publishing, Vienna, pp 342–352Google Scholar
  14. 14.
    Kohl N, Stone P (2004) Policy gradient reinforcement learning for fast quadrupedal locomotion. In: Proceeding of IEEE international conference on robotics and automation 2004 (ICRA 2004), Barcelona, pp 2619–2624Google Scholar
  15. 15.
    Ohroku H, Nonami K (2009) Omni-directional vision and 3D animation based teleoperation of hydraulically actuated hexapod robot COMET-IV. Int J Autom Contr Syst Eng 9(1):17–24Google Scholar
  16. 16.
    Futagami K, Harada Y, Oku M, Ohroku H, Lin X, Okawa K, Sakai S, Nonami K (2008) Real-time navigation and control of hydraulically actuated hexapod robot COMET-IV. In: Proceeding of the 9th international conference on motion and vibration control 2008 (MOVIC 2008), MunichGoogle Scholar
  17. 17.
    Irawan A, Nonami K (2011) Compliant walking control for hydraulic driven hexapod robot on rough terrain. J Robot Mech 23(1):149–162Google Scholar

Copyright information

© Springer Japan 2014

Authors and Affiliations

  • Kenzo Nonami
    • 1
  • Ranjit Kumar Barai
    • 2
  • Addie Irawan
    • 3
  • Mohd Razali Daud
    • 3
  1. 1.Department of Mechanical Engineering Division of Artificial Systems Science Graduate School of EngineeringChiba UniversityChibaJapan
  2. 2.Department of Electrical EngineeringJadavpur UniversityKolkataIndia
  3. 3.Faculty of Electrical and Electronics Engineering Robotics and Unmanned Systems (RUS) groupUniversiti Malaysia PahangPahangMalaysia

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