Hexapod Robots: New CPG Model for Generation of Trajectories

Carla M.A. Pinto*, Diana Rocha*, Cristina P. Santos**
* Instituto Superior de Engenharia do Porto
and Centro de Matematica da Universidade do Porto
Rua Dr Antonio Bernardino de Almeida, 431,
4200-072 Porto, Portugal
** Universidade do Minho
Dept. Electronica Industrial
Campus de Azurem
4800-058 Guimaraes, Portugal
Received 9 December, 2011; accepted in revised form 19 June, 2012
Abstract: Legged robots are often used in a large variety of tasks, in different environments. The
large number of degrees-of-freedom, to be controlled during these tasks, turns the online generation
of trajectories in these robots very complex. In this paper, we consider a modular approach to online
generation of trajectories, based on biological concepts, namely Central Pattern Generators (CPGs).
We introduce a new CPG model for hexapod robots’ rhythms, that generalizes the work of Golu-
bitsky, Stewart, Buono and Collins (1998,1999). Each neuron/oscillator in the CPG consists of two
modules/primitives: rhythmic and discrete, that are modeled by nonlinear dynamical systems. Su-
perposition of discrete and rhythmic primitives permits the modeling of complex motor behaviors,
namely locomotion in irregular terrain and obstacle avoidance. We study the effect on the amplitude
and frequency of the robots’ gaits of superimposing the two motor primitives. The discrete primi-
tive is inserted as an offset of the solution of the rhythmic primitive. We also consider three types
of couplings between CPG units: synaptic, diffusive and mixed. Simulation results reveal interesting
facts, in certain cases amplitude and frequency of periodic solutions, identified with hexapods’ tripod,
caterpillar and metachronal gaits, remain constant. Therefore, it is possible to use these solutions
to generate trajectories for the joint values of real six-legged robots, since varying the joint offset will
not affect the required amplitude and frequency of the resultant trajectory nor the gait.


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