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A client-server architecture for remotely controlling a robot using a closed-loop system with a biological neuroprocessor

This paper introduces an open-source real-time system that remotely controls a robot using human neuroblastoma cultures and a client-server architecture. Multielectrode array set-ups have been designed for direct culturing of neural cells over silicon or glass substrates, providing the capability simultaneously to stimulate and record populations of neural cells. However, it is very difficult to attach these neural cells to the robot structure due to the special conditions of the biological material. The main objective of this research is to build a client-server system for remotely connecting a robot to a neural culture in a closed-loop experimentation. The robot sensors will feed the biological neuroprocessor, while the neural activity will be used for guiding the robot, controlling in this way the robotic behaviour.

On virtual sensory coding: An analytical model of the endogenous representation

In this paper we present a constructive analytical process used to synthesize a net capable of transforming poor sensory data into a more rich internal representation invariant to rotations and local displacements. This model could be of interest both to understand the sensory code and the internalization of external geometries into the nervous system and to build internal models of the environment in autonomous and connectionistic robots.

An analytical method for decomposing the external environment representation task for a robot with restricted sensory information

The problem of modelling and reducing knowledge needed to build an internal representation of the environment is still a milestone in robotics. This representation task is crucial for both understanding perception in humans and programming advanced robots with reasonable navigation skills.In this chapter, we propose an analytical method for decomposing this representation task in terms of a set of primitive inferences. All these inferences race analytical transformations of the sensory data that expand the input space, use rules to compute the centre of areas and polygons of open space and, finally, build a topological graph with possibilities of being updated by learning and used for navigation.The methodological approach followed in this chapter is to search for a library of reusable modelling components that could be used to solve other similar problems of topological representation.

A robotics inspired method of modeling accessible open space to help blind people in the orientation and traveling tasks

The purpose of this paper is to investigate the viability and potential usefulness of a new method of modeling the open space around a blind person. As an alternative or complement to the usual approaches based on the detection of obstacles, we explore the usefulness of offering information on the temporal evolution of the center of area (CA) of safe navigation in relation to the blind persons position. This approach can be considered ergonomic, egocentric and polar, and easy to learn and use.

Inspection method based on multi-agent auction for graph-like maps

Nature teaches us how the collaboration between the members of a herd is an important aspect to ensure their survival as a group. Collaboration requires communication, but it may happen that it could not be established for some reason. In this context, members of the herd have to make decisions on its own, trying to do the best for the group. Inspired by this principle, we have designed a method to overcome the communication difficulties of the environment. The team members compete using their own made decisions, this competition affects on the best possible way to the team benefit.

Study of a multi-robot collaborative task through reinforcement learning

A open issue in multi-robots systems is coordinating the collaboration between several agents to obtain a common goal. The most popular solutions use complex systems, several types of sensors and complicated controls systems. This paper describes a general approach for coordinating the movement of objects by using reinforcement learning. Thus, the method proposes a framework in which two robots are able to work together in order to achieve a common goal. We use simple robots without any kind of internal sensors and they only obtain information from a central camera. The main objective of this paper is to define and to verify a method based on reinforcement learning for multi-robot systems, which learn to coordinate their actions for achieving common goal.

Incremental Building of a Model of Environment in the Context of the McCulloch-Craik's Functional Architecture for Mobile Robots

Current robotics is perhaps the most complete paradigm of applied Artificial Intelligence, since it includes generic tasks involving pluri-sensorial integration and internal representation, as well as motor planning and control. In this paper we revise the architecture proposed by Craik and McCulloch and the concept of environment model introduced by K. Craik. Based on this architecture, which links the description in terms of properties with the selection of a mode of action, we study a simple example application in which an incremental procedure is proposed for the construction and use of a model of a structured medium (the interior of a building) using a graph. The type of graph used to store the descriptions of objects and the relations between them is inspired by the work of Hillier and Hanson on the analysis of interiors. The connections between the elements of the environment (graph nodes) are generated in such a way as to facilitate their efficient use for the selection of the most pertinent mode of action at any given moment. The derivation of the graph is carried out autonomously. In the development of this work, we have avoided as far as possible the use of anthropomorphic terms with no causal connection to the symbol level. Posed in this way, the problem of the representation and use of an environment model by a robot reduces to the use of models of generic tasks and methods at the knowledge level together with graphs and finite state machines at the formal level.

Auction based method for graphic-like maps inspection by multi-robot system in simulated and real environments

Abstract Nature teaches us how the collaboration between the members of a herd is an important aspect to ensure their survival as a group. Collaboration requires communication, but it may happen that it could not be established for some reason. In this context, members of the herd have to make decisions on their own, trying to do the best for the group. Inspired by this principle, we have designed a method to overcome the communication difficulties of the environment. The team members compete using their own decisions, and this competition affects the best possible way for the team to benefit.

Tools for controlled experiments and calibration on living tissues cultures

In recent years, numerous studies attempted to demonstrate the feasibility of using live cell cultures as units of information processing. In this context, it is necessary to develop both hardware and software tools to facilitate this task. The later part is in the aim of this paper. It presents a complete software suite to design, develop, test, perform and record experiments on culture-based biological processes of living cells on multi-electrode array in a reliable, easy and efficient way.