Please Scroll down for Article Connection Science Developmental Robotics: a Survey Developmental Robotics: a Survey

By Max Lungarella, Giorgio Metta, Rolf Pfeifer, Giulio Sandini. 2003

720 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Social Psychology

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Citations in the corpus

Continual Learning for Robotics (2019, background): “From a robotics point of view, CL is the machine learning answer to developmental robotics [93].”
Enactive artificial intelligence: Investigating the systemic organization of life and mind (2009, background): “…programs such as, for example, evolutionary robotics (e.g. Harvey et al. 2005; Nolfi & Floreano 2000), epigenetic and developmental robotics (e.g. Berthouze & Ziemke 2003; Lungarella et al. 2003), and the dynamical systems approach to adaptive behavior and minimal cognition (e.g. Beer 2003; 1995).”
Morphological change in machines accelerates the evolution of robust behavior (2011, result): “This result corroborates observations from learning theory (18, 19) that manually clamping some degrees of freedom in a robot with a fixed body plan, and then gradually releasing them during learning, can accelerate behavior acquisition (20).”
Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints (2013, background): “A central aim of developmental robotics is to study the developmental mechanisms that allow life-long and open-ended learning of new skills and new knowledge in robots and animals (Asada et al., 2009; Lungarella et al., 2003; Weng et al., 2001).”
Intrinsically Motivated Learning in Natural and Artificial Systems (2013, background): “…learning researchers call “autonomous mental development” (Weng et al. 2001), “epigenetic robotics” (Prince et al. 2001), or “developmental robotics” (Lungarella et al. 2003), approaches aiming to develop analogs of the developmental processes that prepare animals over long time periods for a…”
Learning Generalizable Control Programs (2011, methodology): “Computational methods for developmental learning in robotic systems were proposed by a number of researchers including [24] and [1], and have recently enjoyed a great deal of attention in the literature (cf. [13]).”
The role of intersensory redundancy in early perceptual, cognitive, and social development (2012, background): “Work in embodied and developmental robotics (e.g. Arsenio and Fitzpatrick 2005 ; Fitzpatrick et al. 2008 ; Lungarella et al. 2003 ; Weng 2004 ) is advancing our understanding of how sensitivity to intersensory redundancy (particularly audiovisual synchrony) can guide and constrain perceptual,…”
2009 Ieee 8th International Conference on Development and Learning (background): “Developmental robotics approaches are studying mechanisms that may allow a robot to continuously discover and learn new skills in unknown environments and in a lifelong time scale [1], [2].”
Cognitive Developmental Robotics: A Survey (2009, background): “This is one of the biggest differences from artificial systems [23].”
From Motor Learning to Interaction Learning in Robots (2010, background): “Finally, a third line of inspiration takes its sources in developmental psychology, giving rise to the so called developmental robotics or epigenetic robotics [15].”
Bootstrapping bilinear models of Simple Vehicles (2015, background): “D(Y;X;U; ∆) is the set of all discrete-time dynamical systems with sampling interval ∆.”
R-IAC: Robust Intrinsically Motivated Exploration and Active Learning (2009, background): “D EVELOPMENTAL robotics approaches are studying mechanisms that may allow a robot to continuously discover and learn new skills in unknown environments and in a life long time scale [1], [2].”
From hardware and software to kernels and envelopes: a concept shift for robotics, developmental psychology, and brain sciences (2011, background): “In asking how a machine could learn in an open-ended manner, researchers in epigenetic or developmental robotics (Lungarella et al., 2003; Kaplan and Oudeyer, 2006; Asada et al., 2009) partially challenged the basis of the embodied artificial intelligence approach and introduced a methodological…”
An Emergent Framework For Self-Motivation In Developmental Robotics (2004, positive): “A number of robot control architectures have been created using this paradigm [2, 15, 11], many of which involve some form of reinforcement learning.”
Learning Object Affordances: From Sensory--Motor Coordination to Imitation (2008, methodology): “TABLE I LEARNING PHASES OF THE DEVELOPMENTAL APPROACH We adopt a developmental approach [18], [19], where the robot acquires skills of increasing difficulty on top of previous ones.”