Currently, there is an intensive development of bipedal walking robots. The most known
solutions are based on the use of the principles of human gait created in nature during …

In the attempt to build adaptive and intelligent machines, roboticists have looked at
neuroscience for more than half a century as a source of inspiration for perception and …

In this paper, neural network control strategies based on radial basis functions are designed
for biped robots, which includes balancing and posture control. To deal with system …

In this paper, we present our design and experiments on a planar biped robot under the
control of a pure sensor-driven controller. This design has some special mechanical …

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the
biomechanical design with its neuronal control. The coordination of this process is a very …

Agent-based synthetic crowd simulation affords the cost-effective large-scale simulation and
animation of interacting digital humans. Model-based approaches have successfully …

Many multi-agent navigation approaches make use of simplified representations such as a
disk. These simplifications allow for fast simulation of thousands of agents but limit the …

This paper presents the use of Rowat and Selverston-type of central pattern generator
(CPG) to control locomotion. It focuses on the role of afferent exteroceptive and …

It has been shown that sensory morphology and sensory–motor coordination enhance the
capabilities of sensing in robotic systems. The tasks of categorization and category learning …

The achievement of adaptive, stable, and robust locomotion and dealing with asymmetrical
conditions for bipedal robots remain a challenging problem. To address the problem, this …