Architectures for Embodied Imagination

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Functional embodied imagination and episodic memory

The phenomenon of episodic memory has been studied for over thirty years, but it is only recently that its constructive nature has been shown to be closely linked to the processes underpinning imagination. This paper builds on recent work by the authors in developing architectures for a form of imagination suitable for use in artifacts, and considers how these architectures might be extended to provide a form of episodic memory

Architectures for functional imagination

Imagination can be defined broadly as the manipulation of information that is not directly available to an agent's sensors. However, the topic of imagination raises representational, physiological, and phenomenological issues that cannot be tackled easily without using the body as a reference point. Within this framework, we define functional imagination as the mechanism that allows an embodied agent to simulate its own actions and their sensory consequences internally, and to extract behavioural benefits from doing so. In this paper, we present five necessary and sufficient requirements for the implementation of functional imagination, as well as a minimal architecture that meets all these criteria. We also present a taxonomy for categorising possible architectures according to their main attributes. Finally, we describe experiments with some simple architectures designed using these principles and implemented on simulated and real robots, including an extremely complex anthropomimetic humanoid

O.Holland and H.G. Marques. Functional Embodied Imagination and Episodic Memory

The phenomenon of episodic memory has been studied for over 30 years, but it is only recently that its constructive nature has been shown to be closely linked to the processes underpinning imagination. This paper builds on recent work by the authors in developing architectures for a form of imagination suitable for use in artifacts, and considers how these architectures might be extended to provide a form of episodic memory

Soft robotics: The next generation of intelligent machines

There has been an increasing interest in applying biological principles to the design and control of robots. Unlike industrial robots that are programmed to execute a rather limited number of tasks, the new generation of bio-inspired robots is expected to display a wide range of behaviours in unpredictable environments, as well as to interact safely and smoothly with human co-workers. In this article, we put forward some of the properties that will characterize these new robots: soft materials, flexible and stretchable sensors, modular and efficient actuators, self-organization and distributed control. We introduce a number of design principles; in particular, we try to comprehend the novel design space that now includes soft materials and requires a completely different way of thinking about control. We also introduce a recent case study of developing a complex humanoid robot, discuss the lessons learned and speculate about future challenges and perspectives

Self-organisation of motion features with a temporal asynchronous dynamic vision sensor

Neural circuits closer to the periphery tend to be organised in a topological way, i.e. stimuli which are spatially close tend to be mapped onto neighbouring processing neurons. The goal of this study is to show how motion features (optic-flow), which have an inherent spatio-temporal profile, can be self-organised using correlations of precise spike intervals. The proposed framework is applied to the spiking output of an asynchronous dynamic vision sensor (DVS), which mimics the workings of the mammalian retina. Our results show that our framework is able to form a topologic organisation of optic-flow features similar to that observed in the human middle temporal lobe.ISSN:2212-683

From Spontaneous Motor Activity to Coordinated Behaviour: A Developmental Model

In mammals, the developmental path that links the primary behaviours observed during foetal stages to the full fledged behaviours observed in adults is still beyond our understanding. Often theories of motor control try to deal with the process of incremental learning in an abstract and modular way without establishing any correspondence with the mammalian developmental stages. In this paper, we propose a computational model that links three distinct behaviours which appear at three different stages of development. In order of appearance, these behaviours are: spontaneous motor activity (SMA), reflexes, and coordinated behaviours, such as locomotion. The goal of our model is to address in silico four hypotheses that are currently hard to verify in vivo: First, the hypothesis that spinal reflex circuits can be self-organized from the sensor and motor activity induced by SMA. Second, the hypothesis that supraspinal systems can modulate reflex circuits to achieve coordinated behaviour. Third, the hypothesis that, since SMA is observed in an organism throughout its entire lifetime, it provides a mechanism suitable to maintain the reflex circuits aligned with the musculoskeletal system, and thus adapt to changes in body morphology. And fourth, the hypothesis that by changing the modulation of the reflex circuits over time, one can switch between different coordinated behaviours. Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways. Hopping is used as a case study of coordinated behaviour. Our results show that reflex circuits can be self-organized from SMA, and that, once these circuits are in place, they can be modulated to achieve coordinated behaviour. In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.ISSN:1553-734XISSN:1553-735

Synthesising a motor-primitive inspired control architecture for redundant compliant robots

This paper presents a control architecture for redundant and compliant robots inspired by the theory of biological motor primitives which are theorised to be the mechanism employed by the central nervous system in tackling the problem of redundancy in motor control. In our framework, inspired by self-organisational principles, the simulated robot is first perturbed by a form of spontaneous motor activity and the resulting state trajectory is utilised to reduce the control dimensionality using proper orthogonal decomposition. Motor primitives are then computed using a method based on singular value decomposition. Controllers for generating reduced dimensional commands to reach desired equilibrium positions in Cartesian space are then presented. The proposed architecture is successfully tested on a simulation of a compliant redundant robotic pendulum platform that uses antagonistically arranged series-elastic actuation

A Modelling Framework for Functional Imagination.

Imagination is generally regarded as a very powerful and advanced cognitive ability. In this paper we propose a mod- elling framework for what we call functional imagination: the ability of an embodied agent to simulate its own behav- iors, predict their sensory-based consequences, and extract behavioural benefit from doing so. We identify five key com- ponents of architectures for functional imagination, and claim that they may be both necessary and sufficient. We outline a typical architecture, explain the flow of control within it, and describe a typical testing scenario using nested physics-based robot models. We also show how malfunctions within such an architecture may produce effects reminiscent of those found in certain human pathologies