Developmental Robotics (original) (raw)

Developmental robotics: a survey

Connection Science, 2003

Developmental robotics is an emerging field located at the intersection of robotics, cognitive science and developmental sciences. This paper elucidates the main reasons and key motivations behind the convergence of fields with seemingly disparate interests, and shows why developmental robotics might prove to be beneficial for all fields involved. The methodology advocated is synthetic and two-pronged: on the one hand, it employs robots to instantiate models originating from developmental sciences; on the other hand, it aims to develop better robotic systems by exploiting insights gained from studies on ontogenetic development. This paper gives a survey of the relevant research issues and points to some future research directions.

Developmental Robotics: Theory and Experiments

International Journal of Humanoid Robotics, 2004

A hand-designed internal representation of the world cannot deal with unknown or uncontrolled environments. Motivated by human cognitive and behavioral development, this paper presents a theory, an architecture, and some experimental results for developmental robotics. By a developmental robot, we mean that the robot generates its "brain" (or "central nervous system," including the information processor and controller) through online, real-time interactions with its environment (including humans). A new Self-Aware Self-Effecting (SASE) agent concept is proposed, based on our SAIL and Dav developmental robots. The manual and autonomous development paradigms are formulated along with a theory of representation suited for autonomous development. Unlike traditional robot learning, the tasks that a developmental robot ends up learning are unknown during the programming time so that the task-specific representation must be generated and updated through real-time "...

Developmental Robots - A New Paradigm

2002

It has been proved to be extremely challenging for humans to program a robot to such a sufficient degree that it acts properly in a typical unknown human environment. This is especially true for a humanoid robot due to the very large number of redundant degrees of freedom and a large number of sensors that are required for a humanoid to work safely and effectively in the human environment. How can we address this fundamental problem? Motivated by human mental development from infancy to adulthood, we present a theory, an architecture, and some experimental results showing how to enable a robot to develop its mind automatically, through online, real time interactions with its environment. Humans mentally "raise" the robot through "robot sitting" and "robot schools" instead of task-specific robot programming.

Petitagé: A Case Study in Developmental Robotics

2001

In the present paper we describe several autonomous agent architectures developed in the last 5 years, and inspired by mostly by Piaget's genetic epistemology. In the introduction part we give an overview of the developments in AI and robotics after the behaviorist turn in the mid '80s and propose a tentative taxonomy of the approaches that followed according to their treatment of representation. Then we give a brief history of our autonomous agent architecture called Petitagé, tracing its roots from Tolman's to Piaget's works. We describe in detail the schema mechanism, proposed as a way of autonomous environment model building. In the concluding part, we comment on several works from the last 10 years which we consider to be of particular interest to this, developmental branch of robotics and AI.

Developmental robots: Theory, method and experimental results

Proc. 2nd International …, 1999

It is very challenging for humans to program a humanoid robot to act properly in human environment. Humans have a fundamental limitation in constructing an adequate model for the world or an adequate behavior model for the robot, because of the ...

Cognitive developmental robotics as a new paradigm for the design of humanoid robots

This paper proposes cognitive developmental robotics (CDR) as a new principle for the design of humanoid robots. This principle may provide ways of understanding human beings that go beyond the current level of explanation found in the natural and social sciences. Furthermore, a methodological emphasis on humanoid robots in the design of artificial creatures holds promise because they have many degrees of freedom and sense modalities and, thus, must face the challenges of scalability that are often side-stepped in simpler domains. We examine the potential of this new principle as well as issues that are likely to be important to CDR in the future.

The Multiple Roles of Anticipation in Developmental Robotics

2005

Anticipatory systems have been shown to be useful in discrete, symbolic systems. However, non­symbolic anticipatory systems are less well understood. In this paper, we explore the use of anticipation within the framework of connectionist networks to bootstrap from an innate behavior; to drive a reinforcement signal; and to provide feedback on the learnability of a task. Developmental Robotics Developmental robotics is an approach to artificial intelligence that focuses on the autonomous self­ organization of a general­purpose control system. Rather than being programmed to solve a particular task, a robot in the developmental robotics paradigm is programmed to develop sophisticated, self­organized representations and self­motivated behaviors over time. Such a robot begins with nothing but a “seed” program consisting of a simple innate behavior, a motivational system, and a learning system. There is no a priori task to master, only a general goal to develop “mentally” and behaviorall...