Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics

Developmental robotics is an emerging field located at the intersection of developmental psychology and robotics, that has lately attracted quite some attention. This paper gives a survey of a variety of research projects dealing with or inspired by developmental issues, and outlines possible future directions

Adaptivity through alternate freeing and freezing of degrees of freedom

Starting with fewer degrees of freedom has been shown to enable a more efficient exploration of the sensorimotor space. While not necessarily leading to optimal task performance, it results in a smaller number of directions of stability, which guide the coordination of additional degrees of freedom. The developmental release of additional degrees of freedom is then expected to allow for optimal task performance and more tolerance and adaptation to environmental interaction. In this paper, we test this assumption with a small-sized humanoid robot that learns to swing under environmental perturbations. Our experiments show that a progressive release of degrees of freedom alone is not sufficient to cope with environmental perturbations. Instead, alternate freezing and freeing of the degrees of freedom is required. Such finding is consistent with observations made during transitional periods in acquisition of skills in infants

Adaptivity through Physical Immaturity

Given a neural control structure, what would be the impact of body growth on control performance? This question, which addresses the issue of the interaction between innate structure, ongoing developing structure and experience, is very relevant to the field of epigenetic robotics. Much of the early social interaction is done as the body develops and the interplay cannot be ignored. We hypothesize that starting with fewer degrees of freedom enables a more efficient exploration of the sensorimotor space, that results in multiple directions of stability. While not necessarily corresponding to optimal task performance, they will guide the coordination of additional degrees of freedom. These additional degrees of freedom then allow for optimal task performance as well as for more tolerance and adaptation to environmental interaction. We propose a simple case-study to validate our hypothesis and describe experiments with a small humanoid robot

Mapping Information Flow in Sensorimotor Networks

Biological organisms continuously select and sample information used by their neural structures for perception and action, and for creating coherent cognitive states guiding their autonomous behavior. Information processing, however, is not solely an internal function of the nervous system. Here we show, instead, how sensorimotor interaction and body morphology can induce statistical regularities and information structure in sensory inputs and within the neural control architecture, and how the flow of information between sensors, neural units, and effectors is actively shaped by the interaction with the environment. We analyze sensory and motor data collected from real and simulated robots and reveal the presence of information structure and directed information flow induced by dynamically coupled sensorimotor activity, including effects of motor outputs on sensory inputs. We find that information structure and information flow in sensorimotor networks (a) is spatially and temporally specific; (b) can be affected by learning, and (c) can be affected by changes in body morphology. Our results suggest a fundamental link between physical embeddedness and information, highlighting the effects of embodied interactions on internal (neural) information processing, and illuminating the role of various system components on the generation of behavior

Simulating development in a real robot: on the concurrent increase of sensory, motor, and neural complexity

We present a quantitative investigation on the effects of a discrete developmental progression on the acquisition of a foveation behavior by a robotic hand-arm-eyes system. Development is simulated by (a) increasing the resolution of visual and tactile systems, (b) freezing and freeing mechanical degrees of freedom, and (c) adding neuronal units to the neural control architecture. Our experimental results show that a system starting with a low-resolution sensory system, a low precision motor system, and a low complexity neural structure, learns faster that a system which is more complex at the beginning

Simple and low-cost compliant leg-foot system

We describe a simple and low-cost humanoid leg design with compliant joints and springy feet. Mechanical compliance is achieved by combining visco-elastic material with metal. Joints and feet characteristics are evaluated by repeatedly dropping the system from a fixed height. Different joint configurations (silicone rubber, latex and brass) and foot compliance are examined, and additional data are obtained with a Lagrangian analysis of the system. We show that compliance not only reduces impact forces, but also induces smoother joint trajectories

On the interplay between morphological, neural and environmental dynamics: a robotic case study

The robust and adaptive behavior exhibited by natural organisms is the result of a complex interaction between various plastic mechanisms acting at different time scales. So far, researchers have concentrated on one or another of these mechanisms, but little has been done toward integrating them into a unified framework and studying the result of their interplay in a real-world environment. In this article, we present experiments with a small humanoid robot that learns to swing. They illustrate that the exploitation of neural plasticity, entrainment to physical dynamics, and body growth (where each mechanism has a specific time scale) leads to a more efficient exploration of the sensorimotor space and eventually to a more adaptive behavior. Such a result is consistent with observations in developmental psychology