9,106 research outputs found
A multi-touch interface for multi-robot path planning and control
In the last few years, research in human-robot interaction has moved beyond the issues concerning the design of the interaction between a person and a single robot. Today many researchers have shifted their focus toward the problem of how humans can control a multi-robot team. The rising of multi-touch devices provides a new range of opportunities in this sense. Our research seeks to discover new insights and guidelines for the design of multi-touch interfaces for the control of biologically inspired multi-robot teams. We have developed an iPad touch interface that lets users exert partial control over a set of autonomous robots. The interface also serves as an experimental platform to study how human operators design multi-robot motion in a pursuit-evasion setting
A motivational model based on artificial biological functions for the intelligent decision-making of social robots
Modelling the biology behind animal behaviour has attracted great interest in recent years. Nevertheless, neuroscience and artificial intelligence face the challenge of representing and emulating animal behaviour in robots. Consequently, this paper presents a biologically inspired motivational model to control the biological functions of autonomous robots that interact with and emulate human behaviour. The model is intended to produce fully autonomous, natural, and behaviour that can adapt to both familiar and unexpected situations in humanârobot interactions. The primary contribution of this paper is to present novel methods for modelling the robotâs internal state to generate deliberative and reactive behaviour, how it perceives and evaluates the stimuli from the environment, and the role of emotional responses. Our architecture emulates essential animal biological functions such as neuroendocrine responses, circadian and ultradian rhythms, motivation, and affection, to generate biologically inspired behaviour in social robots. Neuroendocrinal substances control biological functions such as sleep, wakefulness, and emotion. Deficits in these processes regulate the robotâs motivational and affective states, significantly influencing the robotâs decision-making and, therefore, its behaviour. We evaluated the model by observing the long-term behaviour of the social robot Mini while interacting with people. The experiment assessed how the robotâs behaviour varied and evolved depending on its internal variables and external situations, adapting to different conditions. The outcomes show that an autonomous robot with appropriate decision-making can cope with its internal deficits and unexpected situations, controlling its sleepâwake cycle, social behaviour, affective states, and stress, when acting in humanârobot interactions.The research leading to these results has received funding from the projects: Robots Sociales para EstimulaciĂłn FĂsica, Cognitiva y Afectiva de Mayores (ROSES), RTI2018-096338-B-I00, funded by the Ministerio de Ciencia, InnovaciĂłn y Universidades; Robots sociales para mitigar la soledad y el aislamiento en mayores (SOROLI), PID2021-123941OA-I00, funded by Agencia Estatal de InvestigaciĂłn (AEI), Spanish Ministerio de Ciencia e InnovaciĂłn. This publication is part of the R&D&I project PLEC2021-007819 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR
Towards an Autonomous Walking Robot for Planetary Surfaces
In this paper, recent progress in the development of
the DLR Crawler - a six-legged, actively compliant walking
robot prototype - is presented. The robot implements
a walking layer with a simple tripod and a more complex
biologically inspired gait. Using a variety of proprioceptive
sensors, different reflexes for reactively crossing obstacles
within the walking height are realised. On top of
the walking layer, a navigation layer provides the ability
to autonomously navigate to a predefined goal point in
unknown rough terrain using a stereo camera. A model
of the environment is created, the terrain traversability is
estimated and an optimal path is planned. The difficulty
of the path can be influenced by behavioral parameters.
Motion commands are sent to the walking layer and the
gait pattern is switched according to the estimated terrain
difficulty. The interaction between walking layer and navigation
layer was tested in different experimental setups
Applications of Biological Cell Models in Robotics
In this paper I present some of the most representative biological models
applied to robotics. In particular, this work represents a survey of some
models inspired, or making use of concepts, by gene regulatory networks (GRNs):
these networks describe the complex interactions that affect gene expression
and, consequently, cell behaviour
A Parallel Distributed Strategy for Arraying a Scattered Robot Swarm
We consider the problem of organizing a scattered group of robots in
two-dimensional space, with geometric maximum distance between robots. The
communication graph of the swarm is connected, but there is no central
authority for organizing it. We want to arrange them into a sorted and
equally-spaced array between the robots with lowest and highest label, while
maintaining a connected communication network.
In this paper, we describe a distributed method to accomplish these goals,
without using central control, while also keeping time, travel distance and
communication cost at a minimum. We proceed in a number of stages (leader
election, initial path construction, subtree contraction, geometric
straightening, and distributed sorting), none of which requires a central
authority, but still accomplishes best possible parallelization. The overall
arraying is performed in time, individual messages, and
travel distance. Implementation of the sorting and navigation use communication
messages of fixed size, and are a practical solution for large populations of
low-cost robots
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