No abstract

New findings in the nervous system of invertebrates have shown how a number of features of central pattern generator (CPG) circuits contribute to the generation of robust flexible rhythms. In this paper we consider recently revealed strategies that living CPGs follow to design CPG control paradigms for modular robots. To illustrate them, we divide the task of designing an example CPG for a modular robot into independent problems. We formulate each problem in a general way and provide a bio-inspired solution for each of them: locomotion information coding, individual module control and inter-module coordination. We analyse the stability of the CPG numerically, and then test it on a real robot. We analyse steady state locomotion and recovery after perturbations. In both cases, the robot is able to autonomously find a stable effective locomotion state. Finally, we discuss how these strategies can result in a more general design approach for CPG-based locomotion.

Abstract-This paper presents a novel mechanism to implement caterpillar-like locomotion. First, the caterpillar-like locomotive pattern in nature is investigated and analyzed systematically. From a biological point of view, caterpillar locomotion can be abstracted as a body wave, called half wave. It is simple, but efficient. In this paper, a novel control mechanism, maintaining the half wave property, is integrated into an improved central pattern generator (CPG) model. For the first time, an asymmetric oscillation is employed on the model for gait generation. The movement is proved stable according to a kinematic analysis. Modulation is able to use to change the shape of the half wave during locomotion. A series of simulation shows the feasibility of using asymmetric oscillators for locomotion. Furthermore, the latest results obtained demonstrate that the proposed asymmetric locomotion mechanism is easy to implement while offering a satisfactory motion performance in on-site experiments.

No abstract

Abstract:Several studies have shown the usefulness of central pattern generator circuits to control autonomous rhythmic motion in robots. The traditional approach is building CPGs from nonlinear oscillators, adjusting a connectivity matrix and its weights to achieve the desired function. Compared to existing living CPGs, this approach seems still somewhat limited in resources. Living CPGs have a large number of available mechanisms to accomplish their task. The main function of a CPG is ensuring that some constraints regarding rhythmic activity are always kept, surmounting any disturbances from the external environment. We call this constraints the "dynamical invariant" of a CPG. Understanding the underlying biological mechanisms would take the design of robotic CPGs a step further. It would allow us to begin the design with a set of invariants to be preserved. The presence of these invariants will guarantee that, in response to unexpected conditions, an effective motor program will emerge that will perform the expected function, without the need of anticipating every possible scenario. In this paper we discuss how some bio-inspired elements contribute to building up these invariants.