Robots as models of evolving systems

The Grossberg Code: Universal Neural Network Signatures of Perceptual Experience

Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code of all biological learning and adaptive intelligence. Low-level representations of multisensory stimuli in their immediate environmental context are formed on the basis of bottom-up activation and under the control of top-down matching rules that integrate high-level, long-term traces of contextual configuration. These universal coding principles lead to the establishment of lasting brain signatures of perceptual experience in all living species, from aplysiae to primates. They are re-visited in this concept paper on the basis of examples drawn from the original code and from some of the most recent related empirical findings on contextual modulation in the brain, highlighting the potential of Grossberg’s pioneering insights and groundbreaking theoretical work for intelligent solutions in the domain of developmental and cognitive robotics.

Pattern formation and flocking for particles near the jamming transition on resource gradient substrates

We numerically examine a bidisperse system of active and passive particles coupled to a resource substrate. The active particles deplete the resource at a fixed rate and move toward regions with higher resources, while all of the particles interact sterically with each other. We show that at high densities, this system exhibits a rich variety of pattern-forming phases along with directed motion or flocking as a function of the relative rates of resource absorption and consumption as well as the active to passive particle ratio. These include partial phase separation into rivers of active particles flowing through passive clusters, strongly phase separated states where the active particles induce crystallization of the passive particles, mixed jammed states, and fluctuating mixed fluid phases. For higher resource recovery rates, we demonstrate that the active particles can undergo motility-induced phase separation, while at high densities, there can be a coherent flock containing only active particles or a solid mixture of active and passive particles. The directed flocking motion typically shows a transient in which the flow switches among different directions before settling into one direction, and there is a critical density below which flocking does not occur. We map out the different phases as function of system density, resource absorption and recovery rates, and the ratio of active to passive particles.

Biomimetic Aquatic Robots Based on Fluid-Driven Actuators: A Review

Biomimetic aquatic robots are a promising solution for marine applications such as internal pipe inspection, beach safety, and animal observation because of their strong manoeuvrability and low environmental damage. As the application field of robots has changed from a structured known environment to an unstructured and unknown territory, the disadvantage of the low efficiency of the propeller propulsion has become more crucial. Among the various actuation methods of biomimetic robots, many researchers have utilised fluid actuation as fluid is clean, environmentally friendly, and easy to obtain. This paper presents a literature review of the locomotion mode, actuation method, and typical works on fluid-driven bionic aquatic robots. The actuator and structural material selection is then discussed, followed by research direction and application prospects of fluid-driven bionic aquatic robots.