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In this paper, dynamical systems made up of locally coupled nonlinear units are used to control the locomotion of bio-inspired robots and, in particular, a simulation of an insect-like hexapod robot. These controllers are inspired by the biological paradigm of central pattern generators and are responsible for generating a locomotion gait. A general(More)
We address the problem of how the survival of cooperation in a social system depends on the motion of the individuals. Specifically, we study a model in which prisoner's dilemma players are allowed to move in a two-dimensional plane. Our results show that cooperation can survive in such a system provided that both the temptation to defect and the velocity(More)
— This paper describes the implementation of a bio-inspired six legged robot: Gregor I. Both structure and lo-comotion control are inspired by biological observations in cockroaches. Robot mechanics attempts to emulate main structural features in cockroaches, like self-stabilizing posture and specializing legged function; in turn, locomotion control is(More)
In this paper we introduce a novel control system architecture for hexapod robots. Our aim is to guarantee efficient horizontal walking and obstacle climbing via suitable postural adjustments. The control scheme takes its inspiration from recent neurobio-logical and kinematic observations of cockroaches walking on a treadmill and climbing over barriers.(More)
We study phase synchronization in a network motif with a starlike structure in which the central node's (the hub's) frequency is strongly detuned against the other peripheral nodes. We find numerically and experimentally a regime of remote synchronization (RS), where the peripheral nodes form a phase synchronized cluster, while the hub remains free with its(More)
—We introduce a new methodology and experimental implementations for real-time wave-based robot navigation in a complex, dynamically changing environment. The main idea behind the approach is to consider the robot arena as an excitable medium, in which moving objects—obstacles and the target—are represented by sites of autowave generation: the target(More)
In this paper, we introduce a network of spiking neurons devoted to navigation control. Three different examples, dealing with stimuli of increasing complexity, are investigated. In the first one, obstacle avoidance in a simulated robot is achieved through a network of spiking neurons. In the second example, a second layer is designed aiming to provide the(More)