Switching Max-Plus models for legged locomotion

We present a new class of gait generation and control algorithms based on the switching max-plus modeling framework that allows for the synchronization of multiple legs of walking robots. Transitions between stance and swing phases of each leg are modeled as discrete events on a system described by max-plus-linear state equations. Different gaits and gait parameters can be interleaved by using different system matrices. Switching in max-plus-linear systems offers a powerful collection of modeling, analysis, and control tools that, in particular, allow for safe transitions between different locomotion gaits that may involve breaking/enforcing synchronization or changing the order of leg lift off events. Experimental validation of the proposed algorithms is presented by the implementation of various horse gaits on a simple quadruped robot.

[1]  Daniel E. Koditschek,et al.  Phase Regulation of Decentralized Cyclic Robotic Systems , 2002, Int. J. Robotics Res..

[2]  Daniel E. Koditschek,et al.  RHex: A Simple and Highly Mobile Hexapod Robot , 2001, Int. J. Robotics Res..

[3]  D. Wilson Insect walking. , 1966, Annual review of entomology.

[4]  R. McN. Alexander,et al.  The Gaits of Bipedal and Quadrupedal Animals , 1984 .

[5]  John Guckenheimer,et al.  The Dynamics of Legged Locomotion: Models, Analyses, and Challenges , 2006, SIAM Rev..

[6]  Geert Jan Olsder,et al.  Synchronization and Linearity: An Algebra for Discrete Event Systems , 1994 .

[7]  R J Full,et al.  Templates and anchors: neuromechanical hypotheses of legged locomotion on land. , 1999, The Journal of experimental biology.

[8]  Jessica K. Hodgins,et al.  Dynamically Stable Legged Locomotion , 1983 .

[9]  R. Weiner Lecture Notes in Economics and Mathematical Systems , 1985 .

[10]  Hiroyuki Kajiwara,et al.  Development of a DES toolbox and its application to a robot-gait planning , 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

[11]  Daniel E. Koditschek,et al.  Robotics in scansorial environments , 2005, SPIE Defense + Commercial Sensing.

[12]  D. F. Hoyt,et al.  Gait and the energetics of locomotion in horses , 1981, Nature.

[13]  S. Grillner Neurobiological bases of rhythmic motor acts in vertebrates. , 1985, Science.

[14]  S. Rossignol,et al.  Neural Control of Rhythmic Movements in Vertebrates , 1988 .

[15]  Christos G. Cassandras,et al.  Introduction to Discrete Event Systems , 1999, The Kluwer International Series on Discrete Event Dynamic Systems.

[16]  Kemal Leblebicioglu,et al.  Free gait generation with reinforcement learning for a six-legged robot , 2008, Robotics Auton. Syst..

[17]  Lin Guo,et al.  A climbing robot with continuous motion , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[18]  Bud Mishra,et al.  Discrete event models+temporal logic=supervisory controller: automatic synthesis of locomotion controllers , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[19]  M Hildebrand,et al.  Symmetrical gaits of horses. , 1965, Science.

[20]  B. De Schutter,et al.  Modelling and control of discrete event systems using switching max-plus-linear systems , 2004 .

[21]  Geert Jan Olsder,et al.  Max Plus at Work-Modelling and Analysis of Synchronized Systems , 2006 .

[22]  Wei Zhao,et al.  Design and CPG-based control of biomimetic robotic fish , 2009 .

[23]  B. De Schutter,et al.  Modelling and control of discrete event systems using switching max-plus-linear systems , 2004 .